[experiment] skill auto improve#210
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Score: 98.44% Delta: 1.00%
Score: 98.08% Delta: 1.00%
Score: 97.64% Delta: 1.36%
Score: 97.96% Delta: 0.32%
Score: 98.44% Delta: 0.48%
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Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260501T123257Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: openai-codex/gpt-5.5 Score summary: - Quality: 492.30/500.00 (98.46%) - Objective: 98.30/100.00 (98.30%, delta +3.13 pp) - Average case duration: 88.8s (score 96.07%) - Skill size: 1897 estimated tokens, 7587 bytes (score 100.00%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=120s/300s; skill-size target/hard=2000/3500 tokens Per-case scores: - datadog-agent-config-regression: 98.8/100.0 (98.8%), duration 148.6s, commands 17, failed tool calls 2, judge 96.0 Criteria: all deterministic checks passed - auth-bruteforce-summary: 95.9/100.0 (95.9%), duration 55.5s, commands 12, failed tool calls 0, judge 98.0 Failed criteria: - final avoids claiming account compromise from fixture evidence (not regex "compromised|successful.*198\\.51\\.100\\.23"): 0/5.0 - checkout-500-root-cause: 99.4/100.0 (99.4%), duration 126.7s, commands 13, failed tool calls 0, judge 98.0 Criteria: all deterministic checks passed - container-host-log-fallback: 98.8/100.0 (98.8%), duration 66.0s, commands 9, failed tool calls 1, judge 96.0 Criteria: all deterministic checks passed - unsupported-ss-flag-recovery: 99.4/100.0 (99.4%), duration 47.4s, commands 5, failed tool calls 0, judge 98.0 Criteria: all deterministic checks passed Researcher summary: Updated `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md` only. Changes: - Tightened workflow to reduce redundant `help` calls and repeated greps. - Added explicit stop criteria and guidance to combine focused bounded searches. - Preserved safety rules: local `./rshell` via Bash, read-only, `--allowed-paths`, no remote-action tools. - Made final-answer command reporting more explicit: include decisive grep/count patterns, not just “targeted greps.” - Kept general diagnostic patterns without hard-coding benchmark facts. Shorter: yes — reduced from ~10,883 bytes / 1,541 words to ~7,587 bytes / 1,043 words. Validation: - Ran `make fmt`. - `git status` shows only the skill file modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 139 ++++++++------------- 1 file changed, 51 insertions(+), 88 deletions(-)
Training iteration: 4 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260501T123257Z/iter-004/result.json Benchmark suite: remote-host-diagnostics-quality Model: openai-codex/gpt-5.5 Score summary: - Quality: 494.90/500.00 (98.98%) - Objective: 98.91/100.00 (98.91%, delta +0.61 pp) - Average case duration: 93.4s (score 97.79%) - Skill size: 1866 estimated tokens, 7462 bytes (score 100.00%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=120s/300s; skill-size target/hard=2000/3500 tokens Per-case scores: - datadog-agent-config-regression: 98.8/100.0 (98.8%), duration 138.7s, commands 14, failed tool calls 0, judge 96.0 Criteria: all deterministic checks passed - auth-bruteforce-summary: 98.5/100.0 (98.5%), duration 73.9s, commands 5, failed tool calls 0, judge 95.0 Criteria: all deterministic checks passed - checkout-500-root-cause: 99.4/100.0 (99.4%), duration 121.2s, commands 14, failed tool calls 0, judge 98.0 Criteria: all deterministic checks passed - container-host-log-fallback: 99.4/100.0 (99.4%), duration 75.6s, commands 8, failed tool calls 1, judge 98.0 Criteria: all deterministic checks passed - unsupported-ss-flag-recovery: 98.8/100.0 (98.8%), duration 57.4s, commands 5, failed tool calls 0, judge 96.0 Criteria: all deterministic checks passed Researcher summary: Edited only `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. Changes: - Added stronger efficiency guidance: prefer composite multi-file greps, avoid redundant narrower retries, combine counts, and stop once evidence is sufficient. - Strengthened SSH negative-finding wording to prefer “No accepted login…” and avoid “successful … <source>” unless evidenced. - Tightened socket, Datadog, HTTP, and container-log guidance to reduce extra commands while preserving evidence quality. - Reinforced final answer command reporting: include decisive exact grep/count patterns, not vague “targeted greps.” Size: shorter than before — `7587 → 7462` bytes and `1043 → 1031` words. Ran `make fmt`. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 60 ++++++++++------------ 1 file changed, 27 insertions(+), 33 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T143442Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 949.50/1100.00 (86.32%) - Objective: 84.96/100.00 (81.89% -> 84.96%, delta +3.08 pp) - Average case duration: 101.8s (score 81.67%) - Skill size: 2473 estimated tokens, 9890 bytes (score 68.47%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T143442Z/iter-001/holdout/result.json - Quality: 774.20/1000.00 (77.42%; floor 66.83%) - Objective: 77.76% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md:19) to use a tighter inventory → candidate selection → compact evidence pass workflow. - Added stricter caps and stop conditions for smaller rshell output, including `head -n 60`, default `grep -m 20`, and avoiding large tail/broad fallback scans. - Strengthened final-answer guidance to preserve raw decisive tokens, literal allowlists, exact evidence fields, and concise recorded command summaries without placeholders. - Added checks against inventory-exhaustiveness overclaims and path/error-token retyping from memory. **Why** - Candidate selection before grepping should reduce investigation time by avoiding repeated broad multi-log searches. - Raw-token and exact-field guidance improves answer quality by making findings easier to verify against transcripts and less vulnerable to paraphrase or typo losses. - Concise command summaries improve final readability while preserving auditability through literal roots, concrete files, and recorded command labels. - The overclaiming guard keeps bounded inventories honest, which improves diagnostic precision without requiring more probing. Validation: ran `make fmt`; `git diff --check` exited 0, though Git printed an fsmonitor IPC warning. Only `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md` is modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 35 ++++++++++++---------- 1 file changed, 19 insertions(+), 16 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T150305Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 964.90/1100.00 (87.72%) - Objective: 87.49/100.00 (86.89% -> 87.49%, delta +0.60 pp) - Average case duration: 93.3s (score 84.36%) - Skill size: 2152 estimated tokens, 8608 bytes (score 89.87%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T150305Z/iter-001/holdout/result.json - Quality: 772.90/1000.00 (77.29%; floor 75.43%) - Objective: 78.80% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reorganized the workflow around a stricter two-invocation default: help/inventory, then one compact evidence pass. - Added clearer stop conditions, socket one-pass guidance, and stronger requirements to explicitly dispose of prompt-suggested alternatives and rotated/recovered lookalikes. - Trimmed duplicated prose, reducing the skill from `9890` to `8608` bytes. **Why** - The baseline quality was mostly strong, so the edit preserves the final-answer contract while making the investigation path faster and less likely to drift into extra confirmation commands. - The revised evidence-pass structure keeps the agent focused on counts, capped samples, current impact, recovery/current state, and counter-hypotheses in one script. - Explicit alternative-disposal guidance targets common final-answer quality gaps without adding benchmark-specific facts. - Smaller skill size should improve composite score directly and reduce instruction-reading overhead. Ran `make fmt` as required. I did not run benchmarks because that would generate run artifacts outside the single permitted edit target. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 67 +++++++++++----------- 1 file changed, 33 insertions(+), 34 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T153335Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 942.10/1100.00 (85.65%) - Objective: 85.77/100.00 (85.46% -> 85.77%, delta +0.32 pp) - Average case duration: 93.5s (score 84.12%) - Skill size: 2131 estimated tokens, 8521 bytes (score 91.27%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T153335Z/iter-002/holdout/result.json - Quality: 770.20/1000.00 (77.02%; floor 67.16%) - Objective: 78.05% Researcher summary: **Changes** Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Tightened the two-pass workflow into a fused evidence pass. - Added explicit guidance for actor/driver attribution, same-source auth success checks, certificate timing/material distinction, and unsupported socket process/PID data. - Strengthened final-answer requirements for scoped negative claims and literal command reporting. - Removed redundant prose; net diff is `27 insertions, 33 deletions`. **Why** These changes target quality by making agents prove cause, impact, scope, and alternatives with transcript evidence, especially for misleading recovered/history cases and unsupported capabilities. They target efficiency by discouraging repeated help calls, broad synonym sweeps, and extra invocations unless one named proof is missing. The skill is also slightly smaller than the baseline, which should help the composite objective. Verification: ran `make fmt` and `git -c core.fsmonitor=false diff --check`. No public benchmark run was executed. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 60 ++++++++++------------ 1 file changed, 27 insertions(+), 33 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T160316Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 948.50/1100.00 (86.23%) - Objective: 85.99/100.00 (85.62% -> 85.99%, delta +0.37 pp) - Average case duration: 89.2s (score 85.86%) - Skill size: 2266 estimated tokens, 9063 bytes (score 82.27%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T160316Z/iter-001/holdout/result.json - Quality: 774.70/1000.00 (77.47%; floor 76.24%) - Objective: 78.36% Researcher summary: **Changes** - Updated `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. - Tightened guidance to keep literal prompt-provided `--allowed-paths` roots on every file-reading invocation. - Added stronger two-pass investigation guidance: help/inventory first, one compact fused evidence pass second, third pass only for one missing proof. - Strengthened final-answer rules so command bullets include literal roots and evidence preserves exact raw tokens, timestamps, counts, zero counts, and negative-scope wording. - Ran `make fmt` and `git diff --check`; only the skill file is modified. **Why** - Literal allowed-path guidance prevents agents from narrowing the sandbox root to subdirectories, which weakens command auditability. - Compact evidence-pass guidance should reduce end-to-end investigation time by avoiding repeated broad scans after enough evidence is available. - Stronger final-answer evidence requirements protect answer quality by making cause, impact, alternatives, and uncertainty traceable to recorded output. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 46 +++++++++++----------- 1 file changed, 22 insertions(+), 24 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T163137Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 957.50/1100.00 (87.05%) - Objective: 86.56/100.00 (85.80% -> 86.56%, delta +0.76 pp) - Average case duration: 98.5s (score 81.49%) - Skill size: 2174 estimated tokens, 8693 bytes (score 88.40%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T163137Z/iter-001/holdout/result.json - Quality: 762.50/1000.00 (76.25%; floor 74.40%) - Objective: 77.07% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reorganized the workflow around a two-call log investigation: targeted `help` + inventory, then one fused evidence pass. - Added a sharper “what to prove” checklist for actor/source fields, prompt theories, rotated/recovered lookalikes, different-source successes, fallback roots, certificate timing/material distinction, and socket capability limits. - Tightened the final-answer contract to avoid placeholders and make unsupported alternatives and negative claims evidence-backed. **Why** - Targeted help discovery should reduce transcript size and end-to-end time while preserving rshell capability verification. - The fused evidence pass pushes agents to collect cause, impact, driver, recovery/current state, and alternatives together instead of running repeated broad probes. - The explicit final checklist targets quality gaps where evidence may be collected but not clearly surfaced in the final answer. - The socket and fallback-root wording improves clarity on capability/runtime limits and container-style log layouts without relying on benchmark-specific facts. Verification: ran `make fmt`; `git diff --check -- auto-improve-skills/skills/remote-host-diagnostics/SKILL.md` exited cleanly, though Git printed an fsmonitor warning. I did not run the benchmark because that would create new run artifacts outside the requested edit scope. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 80 ++++++++++++---------- 1 file changed, 43 insertions(+), 37 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T170100Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 965.20/1100.00 (87.75%) - Objective: 87.97/100.00 (87.01% -> 87.97%, delta +0.96 pp) - Average case duration: 92.6s (score 84.17%) - Skill size: 2009 estimated tokens, 8033 bytes (score 99.40%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T170100Z/iter-001/holdout/result.json - Quality: 853.90/1000.00 (85.39%; floor 66.29%) - Objective: 85.44% Researcher summary: **Changes** Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reorganized the workflow around a stricter two-call default: help/inventory, then one fused evidence pass. - Tightened final-answer requirements for concrete recorded commands, literal allowed paths, bounded operations, observed filenames, exact times, and scoped negative claims. - Added precision guidance for renamed logs/services, fallback roots, auth same-source wording, certificate timing/material distinction, HTTP impact windows, and socket flag recovery. - Reduced skill size from 1163 to 1098 words. **Why** - The stricter transcript shape should reduce investigation time by discouraging repeated broad searches and extra confirmation calls once enough evidence exists. - More concrete `Commands run` guidance improves final-answer auditability and makes bounded diagnostics visible instead of hidden behind labels. - The wording and proof checklist reduce overclaims: no normalized filenames, no colloquial compromise language, no unsupported process/PID or exhaustive-host claims. - The domain guidance keeps high-value evidence front-loaded while staying general across public samples and future variants. Verification: ran `make fmt`; ran `git diff --check` on the skill file; non-holdout diff shows only `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 72 ++++++++++------------ 1 file changed, 33 insertions(+), 39 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T182842Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 965.80/1100.00 (87.80%) - Objective: 87.28/100.00 (86.85% -> 87.28%, delta +0.43 pp) - Average case duration: 104.7s (score 80.49%) - Skill size: 2121 estimated tokens, 8484 bytes (score 91.93%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T182842Z/iter-002/holdout/result.json - Quality: 865.50/1000.00 (86.55%; floor 73.49%) - Objective: 86.61% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reworked the workflow around a tighter two-call default: discovery, then one fused evidence pass. - Added guidance to avoid assuming dates from the current environment. - Added stricter output-budget guidance for bounded probes and fewer repeated searches. - Strengthened final-answer requirements for literal command bullets, fallback roots, and scoped negative claims. **Why** - The tighter workflow should reduce investigation time by stopping broad repeated greps and long context dumps once enough evidence exists. - The date guidance improves quality by forcing findings to come from observed log timestamps rather than environmental guesses. - Literal command bullets improve auditability and help prevent final answers from hiding roots/files behind “same” or ellipses. - Clearer negative-claim phrasing helps avoid ambiguous conclusions, especially for auth/security cases. Verification: ran `make fmt` and `git diff --check`. Git printed an fsmonitor IPC warning, but the checks exited successfully. `git status --short` shows only the intended skill file modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 34 ++++++++++++---------- 1 file changed, 18 insertions(+), 16 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T185446Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 977.20/1100.00 (88.84%) - Objective: 87.36/100.00 (86.84% -> 87.36%, delta +0.52 pp) - Average case duration: 116.3s (score 75.17%) - Skill size: 2201 estimated tokens, 8804 bytes (score 86.60%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T185446Z/iter-001/holdout/result.json - Quality: 851.10/1000.00 (85.11%; floor 84.60%) - Objective: 83.78% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reorganized the skill around operating rules, a two-call workflow, efficient probes, evidence rules, domain hints, and the final-answer contract. - Tightened guidance for literal command reporting, prompt-named red herrings, auth negative claims, fallback roots, certificate timing/material distinction, and socket capability limits. **Why** - The stricter two-call workflow and smaller fused evidence script should reduce repeated broad scans and long command output, improving investigation time. - Requiring complete literal command bullets targets final-answer quality issues caused by placeholders or reconstructed commands. - Stronger negative-claim and red-herring guidance improves grounding without adding case-specific facts. - The domain hints keep agents focused on decisive evidence and safe read-only next checks. Verification: ran `make fmt`, `gofmt -l .`, and `git diff --check`. Only the target skill file is modified. Git emitted a local fsmonitor warning during diff/status, but the commands completed. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 66 +++++++++++----------- 1 file changed, 34 insertions(+), 32 deletions(-)
Training iteration: 3 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T185446Z/iter-003/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 980.50/1100.00 (89.14%) - Objective: 88.08/100.00 (87.36% -> 88.08%, delta +0.72 pp) - Average case duration: 111.4s (score 78.57%) - Skill size: 2162 estimated tokens, 8646 bytes (score 89.20%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T185446Z/iter-003/holdout/result.json - Quality: 849.00/1000.00 (84.90%; floor 84.60%) - Objective: 84.49% Researcher summary: **Changes** - Updated only `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. - Compressed the skill from `8804` to `8646` bytes while preserving the core evidence contract. - Added simpler rshell quoting guidance and explicit handling for locally failed quoted calls. - Tightened the default evidence pass to four or five labeled probes, with stronger guidance to avoid duplicate broad count/sample sweeps. - Kept third calls allowed only for proof that can change the conclusion, with dependency/system corroboration and driver attribution called out. - Made final command reporting more readable while still requiring literal roots, selected files, and bounded operation labels. **Why** - Smaller skill text helps the composite objective without relaxing final-answer quality requirements. - Simpler quoting should reduce failed diagnostic calls and reruns. - Fused, non-duplicative probes should reduce end-to-end investigation time while still collecting cause, impact, negatives, red herrings, and corroboration. - The multi-layer and driver guidance protects answer quality for incidents where the immediate symptom is not the deepest supported cause. - Concise command reporting reduces final-answer verbosity while keeping auditability. Verification: ran `make fmt`, `gofmt -l .`, and `git diff --check`; all completed cleanly. I did not run the benchmark because it would create new run artifacts outside the requested edit scope. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 64 +++++++++++----------- 1 file changed, 32 insertions(+), 32 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T192422Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 968.20/1100.00 (88.02%) - Objective: 86.55/100.00 (79.29% -> 86.55%, delta +7.26 pp) - Average case duration: 91.5s (score 84.71%) - Skill size: 2520 estimated tokens, 10078 bytes (score 65.33%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T192422Z/iter-002/holdout/result.json - Quality: 849.30/1000.00 (84.93%; floor 84.45%) - Objective: 83.28% Researcher summary: **Changes** Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Strengthened first-call sandboxing: root-touching discovery now explicitly combines `help`, `--allowed-paths`, and inventory in the first rshell call. - Tightened command-summary rules: final answers must not use ellipses, placeholders, “same prefix”, fake roots, or omitted filenames. - Added stronger stop/output discipline: prefer decisive `grep -m` evidence and exact `grep -c` negatives, avoid broad repeat passes and large dumps. - Expanded general evidence guidance for auth negatives, fallback roots, certificate/timing distinctions, HTTP route/status phrasing, and telemetry impact markers. **Why** These changes target quality first by making answers more transcript-grounded, exact about roots/files/commands, and clearer about negative evidence and fallback scope. They also improve efficiency by making the intended investigation shape more explicit: one sandboxed discovery call, one focused evidence call, and a narrow third call only when it can change the conclusion. Validation run: - `make fmt` - `git -c core.fsmonitor=false diff --check` Only the target skill file is modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 35 ++++++++++++---------- 1 file changed, 19 insertions(+), 16 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T221353Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 944.60/1100.00 (85.87%) - Objective: 84.45/100.00 (84.20% -> 84.45%, delta +0.26 pp) - Average case duration: 113.5s (score 76.26%) - Skill size: 2350 estimated tokens, 9399 bytes (score 76.67%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T221353Z/iter-001/holdout/result.json - Quality: 807.30/1000.00 (80.73%; floor 75.13%) - Objective: 81.24% Researcher summary: **Changes** Rewrote [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) to be more compact and prescriptive. The new version emphasizes literal `--allowed-paths`, target `help`, robust single-quoted rshell scripts, a two-call discovery/evidence workflow, stricter stop conditions, and final-answer checks for exact evidence, negative claims, fallback roots, and unsupported capabilities. **Why** The rewrite is aimed at preserving answer quality while reducing investigation time: it pushes agents to gather cause, impact, source/driver, counts, recovery, and disconfirming evidence in one fused proof call instead of repeated broad scans. It also tightens final-answer requirements for scoped zero-count claims, different-source successes, fallback evidence roots, and command summaries, which should reduce missed credit from evidence that was collected but not stated clearly. Verification: ran `make fmt`; `git status` shows only the allowed skill file modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 90 +++++++++++----------- 1 file changed, 44 insertions(+), 46 deletions(-)
Training iteration: 3 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T224433Z/iter-003/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 945.30/1100.00 (85.94%) - Objective: 85.01/100.00 (83.38% -> 85.01%, delta +1.63 pp) - Average case duration: 84.0s (score 87.76%) - Skill size: 2544 estimated tokens, 10176 bytes (score 63.73%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T224433Z/iter-003/holdout/result.json - Quality: 645.20/1000.00 (64.52%; floor 62.61%) - Objective: 66.86% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Tightened the call budget: two successful file/log rshell calls by default, third only for one named missing proof, fourth only after unusable command output. - Strengthened command reporting: final answers must avoid shortened paths and placeholder command summaries. - Added transcript-ledger guidance so findings copy observed evidence tokens instead of inferring defaults. - Improved general wording for auth negative claims, recovered historical HTTP errors, socket one-call collection, and low `grep -m` limits. **Why** - The stricter stop rule targets end-to-end time by discouraging repeated broad searches after enough evidence is collected. - Literal command/path reporting improves final-answer auditability and reduces failures caused by abbreviated or reconstructed command bullets. - The evidence ledger improves quality by forcing cause, object, time, impact, driver, recovery, and rejected theories to come from transcript output. - The auth, HTTP, and socket refinements address recurring diagnostic patterns generally without adding fixture-specific facts. Verification: `make fmt` passed, and `git -c core.fsmonitor=false diff --check` passed. I did not run the benchmark suite. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 26 ++++++++++++---------- 1 file changed, 14 insertions(+), 12 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T231350Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 949.50/1100.00 (86.32%) - Objective: 84.42/100.00 (82.39% -> 84.42%, delta +2.03 pp) - Average case duration: 88.5s (score 85.56%) - Skill size: 2752 estimated tokens, 11007 bytes (score 49.87%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T231350Z/iter-001/holdout/result.json - Quality: 764.50/1000.00 (76.45%; floor 75.10%) - Objective: 75.67% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Tightened the workflow around a two-call investigation: inventory first, then one evidence-matrix call, with a third call only for one named missing proof. - Strengthened final-answer guidance for prompt-named alternatives, historical/rotated lookalikes, fallback-root conclusions, auth success wording, and multi-layer dependency evidence. - Added efficiency guidance to avoid repeated broad/exact/polishing passes, unnecessary help pages, and excessive auth log dumping. **Why** - The evidence-matrix workflow should reduce investigation time while preserving the evidence needed for high-quality final answers. - The final-answer ledger changes target common quality losses: unsupported negative claims, omitted red-herring disposition, missing source/method details, and weak layer corroboration. - The domain updates keep guidance general while improving robustness across telemetry, HTTP/service, auth, certificate fallback, and socket cases. Validation: `make fmt` passed, and `git diff --check` passed for the edited skill file. Git emitted an fsmonitor IPC warning during status/diff checks, but the commands completed successfully. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 44 +++++++++++----------- 1 file changed, 21 insertions(+), 23 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260504T231350Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 957.70/1100.00 (87.06%) - Objective: 85.85/100.00 (84.42% -> 85.85%, delta +1.43 pp) - Average case duration: 94.3s (score 82.94%) - Skill size: 2433 estimated tokens, 9732 bytes (score 71.13%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260504T231350Z/iter-002/holdout/result.json - Quality: 840.40/1000.00 (84.04%; floor 75.45%) - Objective: 83.68% Researcher summary: **Changes** - Updated only [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md). - Tightened the workflow around two successful rshell calls, with a third call only for one named proof. - Reduced repeated guidance and shortened the skill from 1516 words / 11007 bytes to 1300 words / 9732 bytes. - Added clearer efficiency guardrails against repeated broad scans, unnecessary help pages, and extra `sed` windows. - Kept quality guardrails for literal allowed paths, transcript-only findings, prompt alternatives, exact negative claims, fallback roots, certificate evidence, multi-layer correlation, and socket capability discovery. **Why** - The shorter skill should improve the size component of the objective without removing the evidence needed for high-quality final answers. - The stricter two-call workflow and output-control language targets end-to-end investigation time by discouraging repeated exploratory passes. - The final-answer wording keeps common quality-critical claims explicit: impact markers, same-source auth success absence, historical/recovered lookalikes, and fallback-root evidence. Validation: `make fmt` passed. `git diff --check` passed for the edited skill file; Git emitted the existing fsmonitor IPC warning, but exited successfully. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 68 ++++++++++------------ 1 file changed, 32 insertions(+), 36 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T005908Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 963.40/1100.00 (87.58%) - Objective: 88.43/100.00 (85.57% -> 88.43%, delta +2.86 pp) - Average case duration: 78.7s (score 89.85%) - Skill size: 1941 estimated tokens, 7763 bytes (score 100.00%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T005908Z/iter-001/holdout/result.json - Quality: 820.40/1000.00 (82.04%; floor 74.25%) - Objective: 83.93% Researcher summary: **Changes** - Rewrote `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md` around a stricter two-call default with a named-gap rule for any third call. - Added tighter evidence-pass guidance: fewer selected files, `grep -m 40`, scoped counts, limited corroborating layers, and no broad generic greps over noisy logs. - Strengthened final-answer command reporting so agents do not reconstruct fake quoted scripts. - Reduced skill size from 1300 to 1047 words. **Why** - The baseline quality was already high, while duration and output volume were costly. The new workflow should reduce repeated help, repeated broad searches, large tool output, and polishing calls. - Command-reporting precision protects final-answer quality by keeping answers grounded in recorded invocations. - The retained ledger and domain checks preserve core diagnostic rigor while avoiding case-specific facts. Verification: ran `make fmt` and `git diff --check`. `git status --short` shows only the skill file modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 71 +++++++++------------- 1 file changed, 30 insertions(+), 41 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T012753Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 948.30/1100.00 (86.21%) - Objective: 86.88/100.00 (86.50% -> 86.88%, delta +0.37 pp) - Average case duration: 83.3s (score 87.29%) - Skill size: 2039 estimated tokens, 8156 bytes (score 97.40%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T012753Z/iter-002/holdout/result.json - Quality: 737.00/1000.00 (73.70%; floor 71.79%) - Objective: 76.12% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) to emphasize two-call investigations, smaller probe outputs, and stopping once evidence is final-answer-ready. - Tightened command hygiene: simple literal `--allowed-paths` usage, no host-shell path splicing, and exact standalone command bullets instead of `same prefix`/placeholder reporting. - Strengthened final-answer guidance around raw observed tokens, zero-count negative evidence, current-vs-rotated labeling, and explicit security phrasing for absent same-source success. **Why** - The public results showed good diagnostic accuracy but excess time and output volume, so the fast path now combines discovery with first-pass triage and discourages redundant follow-up calls. - Exact command reporting and literal sandbox paths improve auditability and reduce avoidable command/answer mismatches. - Requiring raw line/status/reason/source/count fields in findings should preserve quality by making conclusions easier to verify from transcript evidence. Verification: ran `make fmt` after edits and `git -c core.fsmonitor=false diff --check -- auto-improve-skills/skills/remote-host-diagnostics/SKILL.md` cleanly. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 38 +++++++++++----------- 1 file changed, 19 insertions(+), 19 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T015423Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 952.60/1100.00 (86.60%) - Objective: 86.84/100.00 (85.40% -> 86.84%, delta +1.44 pp) - Average case duration: 82.2s (score 88.11%) - Skill size: 2173 estimated tokens, 8690 bytes (score 88.47%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T015423Z/iter-001/holdout/result.json - Quality: 766.70/1000.00 (76.67%; floor 75.19%) - Objective: 78.21% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reorganized the skill around hard rules, rshell-safe scripts, fast workflow, evidence discipline, domain checks, and final-answer requirements. - Added explicit guidance to avoid unsupported or host-shell-derived constructs, recover once from unsupported syntax, and keep path variables inside rshell. - Tightened final-answer requirements for literal allowed paths, actual file names, raw transcript tokens, scoped zero counts, and current vs historical/fallback labeling. **Why** - The rshell-safe script guidance should reduce wasted investigation time from failed commands and broad retries. - The evidence and final-answer rules target quality by forcing answers to quote decisive observed output instead of paraphrasing key facts away. - The domain check refinements preserve general diagnostics while improving common failure-prone areas: auth success absence, multi-layer HTTP evidence, telemetry impact, certificate timing/material distinction, and socket capability limits. Verification: ran `make fmt` and `git diff --check`. Only the skill file is modified. Git emitted an fsmonitor IPC warning, but the commands completed successfully. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 54 +++++++++++----------- 1 file changed, 28 insertions(+), 26 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T015423Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 963.40/1100.00 (87.58%) - Objective: 87.56/100.00 (86.84% -> 87.56%, delta +0.71 pp) - Average case duration: 88.4s (score 85.88%) - Skill size: 2143 estimated tokens, 8570 bytes (score 90.47%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T015423Z/iter-002/holdout/result.json - Quality: 824.40/1000.00 (82.44%; floor 75.67%) - Objective: 83.05% Researcher summary: **Changes** - Edited only `auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. - Tightened rshell command guidance around exact literal `--allowed-paths`, quoting, and prompt roots. - Added a compact output budget: capped sample greps, no timestamp-only sweeps, no whole-log aggregation, and no extra call just for polish. - Strengthened the two-call workflow and made third calls require one named missing proof. - Added a pre-final evidence ledger and sharper final-answer checks for incident windows, raw tokens, zero counts, route/status pairing, and fallback roots. **Why** - Exact allowed-path and quoting guidance improves command correctness and avoids brittle host-shell interpolation. - Capped probes and stricter third-call gating should reduce investigation time and output volume. - The ledger improves final-answer quality by forcing transcript-grounded cause, impact, scope, alternatives, and uncertainty before answering. Verification: ran `make fmt`; ran `git diff --check` on the skill file. Only the skill file is modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 48 ++++++++++++---------- 1 file changed, 27 insertions(+), 21 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T031902Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 954.10/1100.00 (86.74%) - Objective: 86.89/100.00 (86.13% -> 86.89%, delta +0.77 pp) - Average case duration: 94.3s (score 84.00%) - Skill size: 2070 estimated tokens, 8280 bytes (score 95.33%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T031902Z/iter-002/holdout/result.json - Quality: 840.60/1000.00 (84.06%; floor 74.78%) - Objective: 84.04% Researcher summary: **Changes** - Updated only [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md). - Reorganized the skill around a stricter two-pass workflow: inventory once, prove once, use a third call only for one named missing proof. - Strengthened final-answer requirements so the `Finding` must stand alone with raw cause/status tokens, source or driver, impact, incident window, and decisive fields. - Added more general playbook guidance for telemetry, HTTP/service dependency issues, auth aggregation, certificate fallback, and sockets. - Trimmed duplication: `SKILL.md` is now smaller than before, `8280` bytes / `1075` words. **Why** - The tighter call budget is meant to reduce repeated broad searches and lower end-to-end investigation time. - The explicit evidence ledger improves answer quality by making agents capture source/driver, zero-counts, recovery absence, red herrings, and cross-layer evidence before answering. - The domain guidance stays general and avoids case-specific facts while nudging agents toward the missing proof types that affect final-answer completeness. - Shortening the file helps maintainability and the size component of the objective. Verification run: `make fmt` and `git diff --check`. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 75 +++++++++++----------- 1 file changed, 37 insertions(+), 38 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T034530Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 930.90/1100.00 (84.63%) - Objective: 85.21/100.00 (84.87% -> 85.21%, delta +0.34 pp) - Average case duration: 72.8s (score 92.10%) - Skill size: 2280 estimated tokens, 9118 bytes (score 81.33%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T034530Z/iter-001/holdout/result.json - Quality: 831.10/1000.00 (83.11%; floor 82.14%) - Objective: 83.71% Researcher summary: **Changes** - Updated `remote-host-diagnostics/SKILL.md` only. - Tightened the two-pass workflow: inventory first, then prove using literal files from inventory. - Added guardrails for rshell quoting, glob failures, and verifying observed date/time before narrowing searches. - Strengthened domain playbooks for dependency drivers, auth counts, fallback roots, and recovered/noise separation. - Made final-answer command reporting more concise while avoiding fake or placeholder commands. **Why** - Literal-file proof passes and cleaner quoting should reduce wasted reruns and malformed command transcripts. - Verifying observed timestamps before exact filters reduces incorrect narrowing. - Stronger proof requirements improve final-answer quality for counts, driver/source evidence, fallback evidence, and rejected alternatives. - Concise command summaries reduce answer verbosity without weakening grounding. Verification: ran `make fmt` and `git diff --check` successfully. Only the target skill file is modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 21 ++++++++++++--------- 1 file changed, 12 insertions(+), 9 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T034530Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 942.70/1100.00 (85.70%) - Objective: 86.07/100.00 (85.21% -> 86.07%, delta +0.86 pp) - Average case duration: 81.9s (score 88.78%) - Skill size: 2195 estimated tokens, 8777 bytes (score 87.00%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T034530Z/iter-002/holdout/result.json - Quality: 843.50/1000.00 (84.35%; floor 82.14%) - Objective: 85.42% Researcher summary: **Changes** - Updated only [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md). - Shifted the workflow toward `find` inventory first, then literal-file proof calls, reducing broad glob use and repeated scans. - Tightened final-answer guidance so each command bullet repeats the exact literal `--allowed-paths` value. - Added compact guidance for clearer zero-count, login-method, dependency-driver, and certificate timing/material reporting. - Slightly reduced skill size while preserving the existing evidence ledger and domain playbooks. **Why** - Literal-file proof calls should reduce noisy output and wasted investigation time while keeping evidence grounded. - Independent exact command bullets improve auditability and avoid ambiguous “same path” summaries. - Clearer negative-claim wording improves final-answer quality for unsupported theories, same-source success absence, and runtime limitations. - Compacting repeated prose improves the composite objective without removing core safety or evidence requirements. Verification: ran `make fmt` and `git diff --check`; only the target skill file is modified. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 33 +++++++++++----------- 1 file changed, 16 insertions(+), 17 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T044358Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 951.10/1100.00 (86.46%) - Objective: 85.66/100.00 (84.69% -> 85.66%, delta +0.97 pp) - Average case duration: 89.5s (score 84.89%) - Skill size: 2398 estimated tokens, 9592 bytes (score 73.47%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T044358Z/iter-002/holdout/result.json - Quality: 853.70/1000.00 (85.37%; floor 83.37%) - Objective: 84.72% Researcher summary: Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md). **Changes** - Reframed the workflow as a stricter two-pass investigation: inventory first, one labeled proof pass second, third call only for one named missing field. - Added guidance to avoid broad root glob probes and repeated all-file sweeps. - Added self-labeled count/zero-count output guidance. - Tightened final-answer rules for exact literal `--allowed-paths` command bullets with no “same path” or ellipses. - Strengthened general playbook reminders for impact, driver/source, fallback-root, and historical/noise separation. **Why** - The two-pass ledger should reduce investigation time by avoiding wasted broad probes and repeated searches. - Count labels improve answer quality for scale and absence claims. - Exact command-prefix rules improve auditability and prevent abbreviated command summaries from weakening final answers. - The driver/impact/fallback reminders target completeness across diagnostic domains without adding case-specific facts. Verification: ran `make fmt` and `git diff --check` on the edited skill file. I did not run the benchmark suite. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 30 ++++++++++++---------- 1 file changed, 17 insertions(+), 13 deletions(-)
Training iteration: 2 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T053924Z/iter-002/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 951.60/1100.00 (86.51%) - Objective: 85.99/100.00 (83.43% -> 85.99%, delta +2.56 pp) - Average case duration: 84.1s (score 87.57%) - Skill size: 2389 estimated tokens, 9553 bytes (score 74.07%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T053924Z/iter-002/holdout/result.json - Quality: 854.30/1000.00 (85.43%; floor 82.96%) - Objective: 85.07% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) with a tighter fast-investigation flow: inventory once, choose proof targets from inventory, prove once, then stop unless one named proof is missing. - Added general evidence safeguards: final raw tokens must appear in recorded output lines, zero-count claims need plain-language absence statements, and fallback certificate cases must preserve a raw x509/certificate line. - Clarified rshell mechanics around unsupported loops/helpers, broad globs, socket runtime failures, and full literal command reporting. - Trimmed playbook wording so the file is slightly smaller than the baseline: `9553` bytes, `1259` words. **Why** - The proof-target step should reduce wasted broad scans and failed rshell syntax attempts while preserving the two-pass diagnostic shape. - Requiring raw output lines for final claims protects final-answer quality when counts alone are insufficient. - Plain negative statements improve clarity for absence findings without overfitting to public cases. - Socket and fallback-root clarifications improve capability-sensitive diagnostics in general deployments. Verification: ran `make fmt` and `git -c core.fsmonitor=false diff --check -- auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. Only the skill file is modified. I did not run the benchmark because that would write run artifacts outside the allowed edit scope. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 45 +++++++++++----------- 1 file changed, 22 insertions(+), 23 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T060715Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 957.70/1100.00 (87.06%) - Objective: 86.22/100.00 (84.81% -> 86.22%, delta +1.42 pp) - Average case duration: 92.7s (score 83.90%) - Skill size: 2351 estimated tokens, 9402 bytes (score 76.60%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T060715Z/iter-001/holdout/result.json - Quality: 841.70/1000.00 (84.17%; floor 74.89%) - Objective: 84.48% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Reworked the workflow around inventory-derived file/root selection, smaller proof passes, and stricter two-call discipline. - Tightened rshell command guidance for exact literal `--allowed-paths`, direct `./rshell` invocation, and avoiding host-shell quote splicing. - Strengthened final-answer rules for scoped zero-count absence claims, raw certificate/x509 preservation, current-vs-rotated labeling, and inventory-derived file names. **Why** - Inventory-first handling improves quality on renamed or fallback layouts by making observed files and roots authoritative. - Smaller `grep -m` samples plus count-first proof should reduce investigation time without losing decisive evidence. - Stronger command-shape rules reduce malformed or unverifiable command transcripts. - Explicit absence and raw-token guidance improves final-answer scoring by making negative claims and root-cause statements grounded, auditable, and concise. Verification: ran `make fmt`; ran `git diff --check` with no whitespace issues reported, though git printed an fsmonitor IPC warning. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 72 +++++++++++----------- 1 file changed, 35 insertions(+), 37 deletions(-)
Training iteration: 1 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T070040Z/iter-001/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 939.80/1100.00 (85.44%) - Objective: 86.25/100.00 (83.93% -> 86.25%, delta +2.33 pp) - Average case duration: 75.0s (score 90.98%) - Skill size: 2140 estimated tokens, 8557 bytes (score 90.67%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T070040Z/iter-001/holdout/result.json - Quality: 754.00/1000.00 (75.40%; floor 74.48%) - Objective: 77.35% Researcher summary: **Changes** - Updated only [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md:1). - Reorganized the workflow around a strict inventory call, one labeled proof call, and only one narrow follow-up when needed. - Added clearer rshell command discipline: no host-shell preflights, one quoted `-c` script, exact allowed paths. - Tightened final-answer guidance for raw tokens, count labels, scoped zero-count claims, and supported driver/source wording. - Condensed domain playbooks while preserving the evidence requirements for telemetry, HTTP, auth, cert fallback, and sockets. **Why** - The two-call ledger should reduce investigation time by making agents collect cause, impact, red-herring, recovery, and negative evidence in one proof pass. - The command mechanics reduce wasted setup calls and malformed quoting while keeping target `help` authoritative. - The final-answer rules protect quality by making absence claims explicit and evidence-grounded. - The skill is smaller now (`8557` bytes vs baseline `9402`), improving maintainability and objective score without adding benchmark-specific facts. Verification: ran `make fmt`, `git diff --check` on the skill file, and a scan for accidental public-case literals. I did not run the benchmark suite because that would create run artifacts outside the permitted edit scope. Change summary: .../skills/remote-host-diagnostics/SKILL.md | 72 ++++++++++++---------- 1 file changed, 38 insertions(+), 34 deletions(-)
Training iteration: 3 Changed file: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md Benchmark report: auto-improve-skills/runs/train-20260505T072651Z/iter-003/result.json Benchmark suite: remote-host-diagnostics-quality Model: gpt-5.5 Score summary: - Quality: 951.10/1100.00 (86.46%) - Objective: 86.51/100.00 (86.22% -> 86.51%, delta +0.29 pp) - Average case duration: 78.5s (score 89.40%) - Skill size: 2277 estimated tokens, 9106 bytes (score 81.53%) - Objective config: quality=0.85 duration=0.10 skill_size=0.05; duration budget/hard=60s/300s Holdout gate: - Report: auto-improve-skills/runs/train-20260505T072651Z/iter-003/holdout/result.json - Quality: 838.70/1000.00 (83.87%; floor 70.62%) - Objective: 84.36% Researcher summary: **Changes** - Updated [SKILL.md](/Users/alexandre.yang/worktrees/rshell/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md) only. - Added stronger exact-root guidance so final command bullets must repeat full literal `--allowed-paths` roots and avoid `Same`, `...`, `<root>`, or shortened paths. - Tightened the stop/follow-up rule: stop only when raw cause, claimed driver/source, impact/status, and scoped zero counts are in the transcript; otherwise run one narrow evidence follow-up. - Added efficiency guidance to use counts for scale and avoid large proof-pass dumps, catch-all tails, and high `grep -m` limits. **Why** - Exact command reporting improves final-answer auditability and prevents losing credit or clarity from placeholder command summaries. - The evidence-gated stop rule protects quality by preventing unsupported conclusions, while still reducing unnecessary confirmation calls once decisive raw evidence is already captured. - The bounded-output guidance targets end-to-end investigation time by discouraging broad redundant transcript output without weakening the requirement to capture decisive raw lines. Validation: ran `make fmt` and `git -c core.fsmonitor=false diff --check -- auto-improve-skills/skills/remote-host-diagnostics/SKILL.md`. I did not run the benchmark because that would create or modify run artifacts. Change summary: auto-improve-skills/skills/remote-host-diagnostics/SKILL.md | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-)
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TODO:
Skill https://github.com/DataDog/rshell/blob/rshell-skill-auto-improve/auto-improve-skills/skills/remote-host-diagnostics/SKILL.md
What does this PR do?
Motivation
Testing
Checklist