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best-practices-audit

Research-grounded validation of a target (file, directory, or topic) against external best practices and vendor docs. Produces a cited, evidence-grounded comparison.

Stars
141
Source
jmagly/aiwg
Updated
2026-05-31
Slug
jmagly--aiwg--best-practices-audit
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/jmagly/aiwg/HEAD/agentic/code/frameworks/research-complete/skills/best-practices-audit/SKILL.md -o .claude/skills/best-practices-audit.md

Drops the SKILL.md into .claude/skills/best-practices-audit.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Best-Practices Audit

Task

Validate a target — a file, directory, or freeform topic — against current external best practices, vendor documentation, and practitioner discussion. Produce a cited, evidence-grounded comparison report.

This is the research-grounded validation pattern from #929: it institutionalizes the practice of validating against fresh internet sources rather than the model's training-cutoff priors. The improvement is real only when retrieved sources have good signal, so the skill enforces citation guardrails and confidence honesty rather than fabricating breadth.

Parameters

Positional

  • <target> (required): file path, directory, freeform topic, or issue ref

Focus / Scope

  • --focus <area>: security | performance | accessibility | licensing | api-design | testing | docs | ops | compliance | … (open vocabulary)
  • --framework <name>: bias toward a named stack (React, Kubernetes, FastAPI, …)
  • --standard <name>: align to a named standard (OWASP, SOC2, WCAG 2.2, NIST 800-53, …)

Research Budget

  • --recency <window>: default 18 months. Tighten for fast-moving domains, widen for compliance/legal
  • --depth quick|standard|deep: research effort budget (default standard)
  • --sources <list>: restrict to: vendor-docs, standards-bodies, practitioner-blogs, conference-talks, academic, github-discussions
  • --exclude <list>: e.g. exclude SEO-spam domains
  • --cite-threshold <N>: minimum distinct sources before a finding is reported (default 2)

Reporting

  • --dissent: actively surface practitioner disagreement, not just consensus
  • --validate: re-validate existing claims in the target rather than generating new ones
  • --output <path>: where to write the report (CLI handler computes the default)

Pipeline

The CLI handler at src/cli/handlers/best-practices-audit.ts parses flags and computes the output path; this skill receives a fully-formed prompt and runs the research pipeline.

Step 1: Scope

  1. Resolve the target.
    • Path exists? Read the file/directory and enumerate distinct claims or decisions stated in it (architecture choices, dependency selections, pattern usages).
    • Path doesn't exist? Treat as freeform topic — the entire audit is about the topic itself.
  2. Inventory claims. Each claim becomes a unit of evaluation downstream: "we use Tower middleware for retries", "Postgres handles >500K users at the budgeted instance size", "WCAG 2.2 AA is required". For freeform topics, the claim is implicitly "what does current practice say about this topic?".
  3. Apply guidance. --focus and --framework filter which claims are in scope. --validate switches to claim re-verification mode (no generative findings).

Step 1.5: Contributor Discovery (per ADR-023)

Before fan-out, discover any installed framework's kind: research contributors that match the project. The discovery convention is described in ADR-023; the runtime authority is src/contributors/discover.ts and the discovery loop matches the algorithm there.

  1. Read .aiwg/frameworks/registry.json. For each registered framework id, check for <source-path>/research/contributor.md under agentic/code/frameworks/, agentic/code/addons/, or agentic/code/extensions/ (first match wins per ADR-023 §Layout).

  2. Walk .aiwg/contributors/research/*.md for project-local research contributors.

  3. For each candidate, parse YAML frontmatter and validate against the kind: research schema (published at agentic/code/frameworks/research-complete/skills/best-practices-audit/contributor.schema.json).

  4. Run each contributor's detect.glob against the project root. Skip contributors whose detection produces fewer than detect.minCount matches — installed but unused frameworks do not pollute the audit.

  5. For each in-use research contributor, fold its frontmatter into the research plan:

    • focus_areas — intersect with the user's --focus flag if present. If --focus is omitted, use the contributor's full focus list. Multiple contributors' areas merge with union semantics.
    • sources.preferred and sources.exclude — add to the audit's allow / block lists. The user's --sources and --exclude flags take precedence; contributor preferences fill in defaults the user did not specify.
    • recency_default_months — used as the per-contributor default when --recency is not set. When multiple contributors disagree, pick the shorter window (more conservative — fresher sources are a stronger guarantee than older sources).

  6. Stamp origin: <framework-id> on every finding sourced through that contributor's expanded plan. Findings sourced from the generic path (no contributor) get origin: generic. Project-local research contributors stamp origin: project-local.

  7. No regression when no contributors are present. If discovery returns zero in-use contributors, fall through to the bare generic path described in #943 — same behavior as before this issue's wiring landed.

When validate-metadata is available, the schema enforces correctness at deploy time. At audit time, this step trusts validated frontmatter; a contributor that fails parsing or validation is logged and skipped per ADR-023 §Failure mode.

Step 2: Research Fan-Out

Dispatch research per claim/focus area using the AIWG research-complete agents, expanded by any contributor configurations from Step 1.5. Reuse existing capabilities — do not implement parallel research machinery.

Available capabilities (load-on-demand from research-complete):

  • find-sources — discover candidate sources via vendor docs, standards bodies, practitioner channels
  • research-acquire — fetch and process candidate documents
  • research-quality — apply GRADE quality scoring
  • citation-guard — block fabricated citations
  • research-query — query the local research corpus when one is present

If media-curator and the marketing kit are also installed, dispatch them for web-scraping cross-references where appropriate (e.g. practitioner blog comparisons).

Concurrency rule per AIWG context-budget: the agent should issue parallel research tasks where independent (different focus areas, different claims), but not multiplex the same claim into N redundant subagents.

Step 3: Source Quality Gating

For each candidate source returned by research:

  1. Apply --sources allow-list and --exclude block-list.
  2. Run citation-guard to verify the source is real and retrievable (URL reachable, content present at the cited location, not a 404 or redirect to unrelated content).
  3. Apply GRADE methodology via research-quality — score each source as high / moderate / low.
  4. Apply --recency window — sources older than the window are demoted one quality level.
  5. Drop sources that fail any gate. Do not "rescue" weak sources by relaxing thresholds without explicit --guidance to do so.

Step 4: Comparison

For each claim:

  1. Aggregate the surviving sources.
  2. If fewer than --cite-threshold distinct sources support the claim's alignment-or-divergence assessment, downgrade the finding to "weak signal" rather than dropping it silently. Users need to see when the corpus didn't support a strong conclusion — that is itself a finding.
  3. Determine alignment: ALIGNED / PARTIAL / DIVERGES / CONTESTED.
  4. With --dissent, also extract dissenting voices: who argues the other way, where, and on what grounds. Surface these as a labeled section, not a footnote.

Step 5: Report

Write to the output path computed by the CLI handler. Structure per #929 §5:

# Best-Practices Audit: <target>

**Generated**: YYYY-MM-DD
**Focus**: <flags or 'all'>
**Depth**: <flag>
**Cite threshold**: <N>

## Executive Summary

<2–4 sentences: what's aligned, what's misaligned, overall confidence>

## Findings

### Finding 1: <claim or decision under review>

- **Current state in project**: <quote/paraphrase with file:line if available>
- **Current industry practice**: <summary>
- **Alignment**: ALIGNED | PARTIAL | DIVERGES | CONTESTED | WEAK SIGNAL
- **Confidence**: high | moderate | low
- **Evidence**:
  - [S1] <source title> — <vendor/standards body/blog>, <date>, <url>
  - [S2] ...
- **Recommendation**: <specific change or 'keep as-is, well-justified by
  current practice'>

(repeat per claim)

## Dissenting Views / Open Debates

<where practitioners disagree and why — empty section is acceptable when
nothing surfaced; do not invent dissent>

## Sources

Full bibliography with retrieval dates. Every source cited above must
appear here with full provenance. No citation appears in Findings without
appearing in Sources.

## Methodology Notes

- Research depth: <quick|standard|deep>
- Recency window: <window>
- Sources excluded: <list, including domains blocked by --exclude>
- Sources unavailable: <list, with reason — e.g. paywalled, 404>

Anti-Hallucination Guardrails (Hard Requirements)

These are non-negotiable. Failure to meet any of these breaks the audit's core value proposition.

  1. No fabricated citations, DOIs, URLs, or quotes. Every cited URL must be the result of a retrieval that returned content at that URL. citation-guard enforces this; if citation-guard is unavailable, the audit must surface that fact in Methodology Notes and downgrade overall confidence.
  2. Cite-threshold is enforced, not advisory. A finding below threshold is downgraded to WEAK SIGNAL or dropped — never reported as if the threshold were met.
  3. Conflicting sources surface as labeled disagreement. If sources A and B disagree, the report says so explicitly. The audit does not silently pick one and pretend consensus.
  4. Sparse signal is reported honestly. When the corpus is thin or weak, the report says so and downgrades confidence. The audit does not fill the void with the model's training-data priors.
  5. Training-data-only claims are marked. Any background context the audit relies on without a citation is labeled (no external citation verified) so the reader knows what's grounded vs what's not.
  6. --validate mode never generates new findings. It only re-checks claims already present in the target. If a claim's supporting source is no longer reachable or has changed, the audit reports that the claim is now unverified, not that there's a new claim to make.

Out of Scope (deferred per #929)

  • Cache layer for repeated audits — see deferred tracker #946 (caching applies to contributor discovery; research caching is a separate concern but not in scope for this skill)
  • Auto-ingest into the knowledge-base framework — defer until best-practices-audit has been used in anger and we can see whether ingestion is valuable (#929 open question 4)
  • (Contributor-driven prompt expansion now wired in — see Step 1.5 above. The earlier "deferred" note from #943 is resolved by #944.)

References

  • @.aiwg/architecture/decisions/ADR-023-contributor-discovery-convention.md — the contributor convention #944 will wire into this skill
  • @$AIWG_ROOT/agentic/code/frameworks/research-complete/skills/find-sources/SKILL.md — source discovery
  • @$AIWG_ROOT/agentic/code/frameworks/research-complete/skills/research-acquire/SKILL.md — source retrieval and processing
  • @$AIWG_ROOT/agentic/code/frameworks/research-complete/skills/research-quality/SKILL.md — GRADE methodology
  • @$AIWG_ROOT/agentic/code/frameworks/research-complete/skills/citation-guard/SKILL.md — fabricated-citation detection
  • @$AIWG_ROOT/agentic/code/frameworks/research-complete/skills/research-query/SKILL.md — local corpus queries
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/research-before-decision.md — research-first rule the audit's pipeline implements
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/context-budget.md — parallel subagent limits applied during research fan-out