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Get Started Free →Use when a skill is brittle, drifting, repeatedly failing, or needs a Reliable Skill Contract. Trigger for phrases like skill lifeguard, reliable skill, self-maintaining skill, negative examples, verification checkpoints, drift signals, replay hooks, or failure log to skill patch. Audits or patches skills so high-value workflows include explicit forbidden behaviors, checkpoints, machine-checkable done conditions, replay or smoke hooks, and drift detection.
.claude/skills/majiayu000-skill-lifeguard/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 26% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -2% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -5% | 0% |
| case-22 | ✗→✓ | ▲ Improved | 363% | 0% |
| case-13 | ✓→✓ | = Same ✓ | 64% | 0% |
Use this skill to make an existing or new skill self-maintaining enough for real agent work. It complements skill-audit and skill-creator: use this skill for the reliability contract, then use those skills for library fit and authoring.
Read references/examples.md when you need example contract wording. Use assets/reliable-contract-template.md when drafting a reusable section.
Every high-value workflow skill should either include these five elements or record why an element is intentionally deferred:
| Element | Required Evidence | | --- | --- | | Explicit negative examples | Named forbidden behaviors and concrete alternatives. | | Verification checkpoints | Pass/fail checks after important phases, not only at the end. | | Machine-checkable done conditions | Commands, assertions, artifacts, or state queries from the current session. | | Replay or smoke hooks | A small way to rerun or sample the workflow, plus a log-to-patch loop. | | Drift signal detection | Observable signs that the skill is stale, undertriggering, overtriggering, or producing false success. |
manual: workflow still needs human validation.skill: manually validated and packaged as reusable instructions.automation: repeatedly reliable and safe enough for scheduled or hook-driven use.present, partial, missing, or deferred.SKILL.md for routing and boundaries,references/ for long examples, scripts/ for deterministic checks, assets/ or templates/ for reusable report shapes.
instructions, and run local validation.
deleting user files, changing secrets, or promoting manual workflows into scheduled automation.
verification, replay hooks, or drift signals.
smoke runs into a skill patch and rerun validation.
incomplete or misleading.
For audits, lead with findings:
textreliable_skill_contract: - target: - maturity: - score: negative_examples: verification_checkpoints: machine_done_conditions: replay_or_smoke_hooks: drift_signals: - blocking_gaps: - patch_plan: - verification:
For edits, keep the patch scoped to the missing contract elements. Do not rewrite the skill's domain behavior unless the reliability gap requires it.
Reject these patterns and name the safer alternative:
query instead.
failure or mark the workflow blocked.
an allowed replacement.
manualmaturity and add smoke checks first.
Place checkpoints where a future agent could otherwise drift:
Treat these as evidence to patch the skill:
For Spellbook skills, run:
bashpython3 ./scripts/validate_skills.py --check python3 ./scripts/audit_skill_quality.py skill-name
If the skill owns scripts, also run the relevant syntax check or fixture. Report missing prerequisites instead of marking the contract complete.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-13 | pass→pass | 8,701 | 6,641 | -24% | 1 | 1 | 0% | 1,272 | 2,082 | +64% | 0 | 0 | — |
case-01 | fail→fail | 30,489 | 5,170 | -83% | 1 | 1 | 0% | 5,611 | 1,257 | -78% | 0 | 0 | — |
case-02 | fail→fail | 20,056 | 5,714 | -72% | 1 | 1 | 0% | 3,335 | 1,413 | -58% | 0 | 0 | — |
case-03 | fail→fail | 26,871 | 5,252 | -80% | 1 | 1 | 0% | 4,671 | 1,327 | -72% | 0 | 0 | — |
case-04 | fail→pass | 8,399 | 3,547 | -58% | 1 | 1 | 0% | 1,306 | 1,642 | +26% | 0 | 0 | — |
case-05 | pass→pass | 9,422 | 2,529 | -73% | 1 | 1 | 0% | 1,504 | 1,439 | -4% | 0 | 0 | — |
case-06 | pass→pass | 12,025 | 2,220 | -82% | 1 | 1 | 0% | 1,818 | 1,385 | -24% | 0 | 0 | — |
case-07 | fail→pass | 9,499 | 2,904 | -69% | 1 | 1 | 0% | 1,607 | 1,579 | -2% | 0 | 0 | — |
case-08 | pass→pass | 5,798 | 2,687 | -54% | 1 | 1 | 0% | 868 | 1,465 | +69% | 0 | 0 | — |
case-14 | pass→pass | 13,769 | 6,905 | -50% | 1 | 1 | 0% | 2,149 | 2,130 | -1% | 0 | 0 | — |
case-09 | pass→pass | 6,986 | 2,386 | -66% | 1 | 1 | 0% | 1,061 | 1,422 | +34% | 0 | 0 | — |
case-10 | pass→pass | 7,400 | 3,012 | -59% | 1 | 1 | 0% | 1,093 | 1,485 | +36% | 0 | 0 | — |
case-11 | fail→pass | 10,811 | 3,097 | -71% | 1 | 1 | 0% | 1,587 | 1,511 | -5% | 0 | 0 | — |
case-12 | pass→pass | 9,450 | 2,544 | -73% | 1 | 1 | 0% | 1,324 | 1,411 | +7% | 0 | 0 | — |
case-15 | pass→pass | 9,217 | 4,618 | -50% | 1 | 1 | 0% | 1,333 | 1,691 | +27% | 0 | 0 | — |
case-16 | pass→pass | 6,459 | 5,339 | -17% | 1 | 1 | 0% | 997 | 1,924 | +93% | 0 | 0 | — |
case-17 | pass→pass | 14,374 | 7,113 | -51% | 1 | 1 | 0% | 2,232 | 2,077 | -7% | 0 | 0 | — |
case-18 | pass→pass | 7,291 | 3,559 | -51% | 1 | 1 | 0% | 1,030 | 1,567 | +52% | 0 | 0 | — |
case-19 | pass→pass | 12,555 | 5,218 | -58% | 1 | 1 | 0% | 1,921 | 1,856 | -3% | 0 | 0 | — |
case-20 | pass→pass | 12,670 | 6,451 | -49% | 1 | 1 | 0% | 1,847 | 2,024 | +10% | 0 | 0 | — |
case-21 | pass→pass | 12,450 | 10,372 | -17% | 1 | 1 | 0% | 2,040 | 2,644 | +30% | 0 | 0 | — |
case-22 | fail→pass | 6,276 | 20,367 | +225% | 1 | 1 | 0% | 904 | 4,186 | +363% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +18 percentage points is the difference between those two pass rates over the 19 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.