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Gold standard

Skill HetCreep/CoalMine/skills/gold-standard

Nine quality-canary skills for AI coding agents - code health, world-class rule completeness, grounding, supply chain, resilience, drift & more - plus the auto-cadence hooks that run them unprompted at session start and session end. Cross-agent, consent-gated, token-lean.

Install
npx -y skills add HetCreep/CoalMine --skill gold-standard

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  • 11 stars11 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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World-class completeness audit — score a project's rules/standards/features against best-in-class exemplars, name the gaps, fill missing rules, adopt as binding, then offer to conform existing code. Triggers on keywords: "/gold-standard", "gold-standard", "audit rules", "are we world-class", "fill gaps", "complete our rules", "conform old code".

SKILL.md

5.7 KB, as published. Nobody here has run it

Gold Standard

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Answer: "For a project that does THIS — are rules/standards/features 100% vs world-class? If not, what's missing?"

Four acts: AUDITFILLADOPTCONFORM. Stop at any.

Manual /gold-standard = interactive setup: read references/wizard.md (dual-audience — layman 1-question default · programmer order→bill→pay). The auto/keyword path (the Triggers table) skips it.

Triggers

KeywordAct
"audit rules" / "gold-standard" / "are we world-class"AUDIT
"fill gaps" / "complete our rules"FILL
"work by these rules" / "follow from now on"ADOPT
"conform old code" / "retrofit"CONFORM
"fill and adopt" / ACTION=fill-adoptAUDIT → FILL → summary → ADOPT → offer CONFORM

Acts

ADOPT and every CONFORM fix are gated through ask_question — never assume approval.

  1. AUDIT — pick 3–5 named exemplars fresh at run time (the bar moves with the era — never reuse a remembered bar), derive the 100% checklist per dimension, score (✅/🟡/❌/N-A), give overall %. Previously filled/adopted rules are audit subjects too: a rule past its revalidate due date or contradicted by today's exemplars is a gap.
  2. FILL — write missing MUST-HAVE rules into the project's rules home (.claude/rules/AGENTS.mdSTANDARDS.md). Match project style + voice. Cite the exemplar. Invoke source-grounding for version-sensitive claims. Extend existing; never duplicate. Check the retired-rules record first — never resurrect a rule retired with a reason unless the user overrides. No overkill rules — only essential, practical, saturated ones. Stamp each rule: <!-- coalmine: verified <YYYY-MM-DD> · exemplar <name> · revalidate <30|90>d --> — 30d for fast-moving surfaces (agent platforms, model/API versions), 90d for general engineering. CVE/advisory rules re-validate on the advisory EVENT first; their 30d stamp is only the staleness backstop. Event override beats the calendar. (Rationale: references/method.md.)
  3. ADOPT — treat the completed ruleset as binding for the rest of the session. Code changes still need user approval — adoption governs how to work, not license to auto-edit.
  4. CONFORM — scan existing code against adopted rules; report violations (path:line · rule · evidence). Fix on approval: checkpoint → one fix → build+tests → revert if newly red. Style Drift: conform minority patterns to the dominant style (highest average usage); never start a standalone style refactor.
  5. RE-VALIDATE (runs inside every repeat AUDIT, or when offered on a past-due stamp) — verdict each CoalMine-stamped rule, all changes choice-gated:
    • still valid → re-stamp the date, touch nothing else (no churn);
    • stale but needed → rewrite against today's exemplar;
    • obsolete (subject removed, platform died, or substance merged into another rule) → delete the rule + record a one-line tombstone in the project's memory/decision log (retired <rule> <date>: <reason>) — dead rules burn context every session; the tombstone blocks the next FILL from resurrecting them.
    • CONSISTENCY (the agent trusts memory/rules it never verifies — so verify them): scan the memory/decision log and any in-repo rule register for (a) a prescribed fix/"decision" that contradicts a binding rule or another decision (e.g. prescribing randomness where a determinism rule forbids it) — a poisoned/stale entry; (b) references to a file, flag, or command that no longer exists. Flag each with the conflicting source quoted; correct only through the choice-gate. This is the semantic half; the mechanical half (node scripts/consistency.mjs: cross-document counts, byte-identical doctrine mirrors, well-formed stamps) runs without an agent.

Exemplar-picking rules, scorecard mechanics, stamp/tombstone formats: read references/method.md before the first AUDIT.

Method

  1. Bar — name 3–5 world-class exemplars + why them (cite real programs, not "best practices").
  2. Checklist — MUST-HAVE (table-stakes) vs EXCELLENCE (top-tier polish). Each tied to an exemplar.
  3. Score — every criterion. 🟡 = half credit. N-A must be justified; unjustified N-A = ❌.
  4. Gaps — prioritized: MUST-HAVEs first. Each: criterion · exemplar · effort · impact.

Dimensions (pick relevant)

Correctness · Security · Performance · UX/DX · Docs/onboarding · Testing/CI · Distribution/integrity · Observability · Governance/licensing · Maintainability · Compatibility · Error handling

Discipline

  • Don't inflate. 85% should say 85%.
  • Every criterion cites a real exemplar — "npm does X", "Cargo does Y". No unsourced "best practice".
  • State dimensions not assessed + why.
  • Blocked lookups: if sandbox/network blocks an external check, mark it N-A with justification — never guess.
  • Multi-source grounding: never score from memory or a single source — cross-reference exemplars, registries, advisory feeds (GHSA/OSV/NVD).

Output

  1. Bar — category + named exemplars
  2. Scorecard — | dimension | criterion | tier (must/excellence) | exemplar | status | evidence |
  3. Per-dimension % + overall % (list N-A exclusions)
  4. Gaps — criterion · exemplar · effort · impact
  5. Verdict — 1 line + top 3 moves
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Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.