Meta maintain config

AI Configuration Maintenance

Keep .claude/ directory living knowledge base. Stay current with project + AI tooling best practices.

Read .claude/rules/meta-ai-config.md first — defines conventions, budget constraints, anti-patterns this skill enforces.

Modes

create — New Artifact

1. Discover + Research — Invoke canonical multi-agent research primitive from /swarm-plan (Phases 1-2). Spawn workers parallel:

   • worker-explorer (1-2): existing .claude/ patterns, conventions, cross-references, neighbors of artifact
   • worker-researcher (1-3, split by axis): Claude Code docs (code.claude.com/docs), domain best practices, community patterns for artifact topic

   Persist substantial findings as .claude/artifacts/research_[topic].md for reuse. See /swarm-plan "Research as a Reusable Primitive".

2. Draft — Follow meta-ai-config.md conventions:

   • Respect context budget (<200 lines rules, <500 lines skills)
   • Use paths: scoping for rules unless truly global
   • Skills: write description as "what + when to use" (max 1024 chars)
   • Use progressive disclosure — SKILL.md overview, reference files for detail
   • Add disable-model-invocation: true for action skills with side effects

3. Integrate — Update CLAUDE.md tables, meta-rule inventory

4. Validate — Run audit checks (see below)

audit — Check All Artifacts

Context budget audit:

• CLAUDE.md under 200 lines?
• Each global rule under 200 lines?
• Count global rules — too many degrades performance
• Skill descriptions total within 2% context budget?

Structural audit:

• Every SKILL.md has name + description?
• No allowed-tools in skill frontmatter?
• All persona skills have user-invocable: true?
• Hook scripts executable?

Dead glob audit:

• For each scoped rule, do paths: patterns match existing files?
• After directory renames, glob patterns silently fail — verify with: find . -path "pattern" | head -1

Cross-reference audit:

• Rules referencing other rules → targets exist?
• Skills referencing rules → correct filenames?
• Agents referencing rules → still valid?

Duplication audit:

• Same instruction in CLAUDE.md AND rule? (single source of truth)
• Same domain knowledge in skill AND rule? (skill for on-demand, rule for always-on)

refresh — Sync AI Knowledge with Codebase

1. Detect drift — Spawn worker-explorer agents:

   • Public types in subsystem-*.md still exist in code?
   • New modules/crates lacking subsystem rules?
   • Error variants, trait names, method signatures still match?
   • CLI commands changed (new flags, subcommands)?
   • deny.toml / .licenserc.toml changed?

2. Research updates — Spawn worker-researcher:

   • Claude Code docs for new features (hooks, frontmatter, agents)
   • New best practices in Rust, async, testing, security
   • Check if meta-ai-config.md needs updating

3. Update stale artifacts — Read current code, update with accurate info, preserve structure

4. Self-update — Check if this skill (meta-maintain-config) or meta-ai-config.md outdated per research findings. Update them too.

5. Validate — Run audit mode

review — AI Config Quality Review

Review recent changes to .claude/ for quality:

1. Context budget — Change increase always-loaded context? Justified?
2. Scoping — Could this global rule be path-scoped instead?
3. Progressive disclosure — SKILL.md body under 500 lines? Move details to reference files?
4. Description quality — Skill description specific enough for auto-discovery?
5. Anti-patterns — Check against 8 anti-patterns in meta-ai-config.md
6. Consistency — Change follow existing artifact conventions?
7. Reusability — Hook more appropriate than rule? (deterministic + zero context cost)

catalog-sync — Catalog Drift Review

When auditing AI config, verify .claude/rules.md reflects reality:

1. Every rule in .claude/rules/*.md has entry in .claude/rules.md
2. Every catalog entry resolves to real file
3. CLAUDE.md still links to catalog
4. "By concern" table reflects current development axes (add rows for new concerns; remove for retired)
5. "By auto-load path" table matches actual paths: frontmatter in each rule file

Run task claude:tests — structural tests catch most drift automatically (test_catalog_covers_all_rules, test_catalog_references_resolve, test_claude_md_points_to_catalog). Manual review catches semantic drift (e.g., new concern worth catalog row even if no test complains).

research — Deep-Dive Topic

Invoke canonical multi-agent research primitive from /swarm-plan (Phases 1-2). No reinvent.

1. Spawn workers parallel — per /swarm-plan Phase 2 axis-splitting:

   • worker-researcher × 2-3, split by axis:
     • Tooling axis — Claude Code / AI tooling best practices
     • Domain axis — Rust patterns, OCI spec, cargo-deny, etc.
     • Community axis — how other projects handle this
   • worker-explorer (optional) — ground external findings in existing .claude/ artifacts

2. Synthesize → Actionable guidance. Persist as .claude/artifacts/research_[topic].md

3. Apply → Update relevant artifacts

Refresh Targets

Artifact	What goes stale	Refresh trigger
subsystem-*.md rules	Types, paths, signatures, error variants	After refactors, new modules
quality-rust.md (+ other quality-*.md)	Language anti-patterns, async conventions, 2026 updates	After edition/release updates, new tooling
arch-principles.md	Design principles, ADR index, code style conventions	After new patterns, new modules
Persona skills	Implementation patterns, fixtures, commands	After new commands, workflows
Agent definitions	Patterns, self-review checklists	After quality-*.md changes
deps	License allowlist, tool versions	After deny.toml changes
CLAUDE.md	Build commands, env vars, layout	After new crates, env vars
meta-ai-config.md	Conventions, budget numbers, anti-patterns	After Claude Code releases
This skill	Modes, workflow, refresh targets	After Claude Code releases

Maintenance Schedule

Frequency	Action
Every feature branch	audit before merging AI config changes
Monthly	refresh to detect drift
On Claude Code update	research "Claude Code new features" then self-update
On new tool integration	create for tool's skill/rule, then audit
When something feels off	review recent changes

Constraints

• ALWAYS research online before creating AI artifacts
• ALWAYS spawn at least one worker-researcher for domain knowledge
• ALWAYS check context budget impact (adding always-loaded context?)
• NEVER remove artifacts without checking cross-references first
• NEVER edit settings.json hooks without testing hook script
• Prefer hooks over rules for enforcement (deterministic + zero context cost)
• Commits use chore: prefix (per project convention)