research-lint
Run the research corpus lint ruleset to detect structural and referential integrity issues — orphan notes, missing frontmatter, broken references, missing GRADE assessments.
Best use case
research-lint is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Run the research corpus lint ruleset to detect structural and referential integrity issues — orphan notes, missing frontmatter, broken references, missing GRADE assessments.
Teams using research-lint should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-lint/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-lint Compares
| Feature / Agent | research-lint | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Run the research corpus lint ruleset to detect structural and referential integrity issues — orphan notes, missing frontmatter, broken references, missing GRADE assessments.
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Research Lint Run the research corpus lint ruleset against `.aiwg/research/` to detect structural and referential integrity issues. ## Triggers - "lint the research corpus" - "check research integrity" - "validate research notes" - "sweep the corpus for issues" - "research lint" - `/research-lint` ## Parameters ### `[target]` (optional) Path to lint. Defaults to `.aiwg/research/`. ### `--fix` (optional) Attempt auto-fixes for fixable issues (add missing frontmatter defaults, correct formatting). ### `--format` (optional) Output format: `full` (default), `summary`, or `json`. ### `--ci` (optional) CI mode — exit code reflects pass/fail. ### `--fail-on` (optional) Severity threshold for failure: `error` (default), `warn`, or `info`. ## Execution Flow ### Phase 1: Run Lint Execute the lint runner against the research corpus: ```bash aiwg lint .aiwg/research/ --ruleset research --format full ``` This checks all 11 rules in the research ruleset: | Rule | Severity | What it checks | |------|----------|---------------| | `ref-frontmatter` | error | Required frontmatter fields present | | `ref-id-unique` | error | No duplicate REF-XXX identifiers | | `ref-id-format` | warn | REF identifiers follow `REF-NNN` naming | | `citation-resolves` | error | REF-XXX references point to existing notes | | `grade-present` | warn | GRADE quality assessment in frontmatter | | `provenance-present` | warn | Provenance metadata present | | `cross-ref-bidirectional` | info | Related refs linked both ways | | `orphan-detection` | info | Notes with no inbound references | | `frontmatter-date-format` | warn | Dates follow ISO 8601 | | `source-file-exists` | error | Referenced source files exist | ### Phase 2: Report Results Display the results grouped by file with severity indicators: - Errors: must be fixed for corpus integrity - Warnings: should be addressed for corpus quality - Info: suggestions for improvement ### Phase 3: Auto-Fix (if --fix) When `--fix` is specified, attempt automatic corrections: 1. **Missing frontmatter fields** — Add fields with sensible defaults: - `status: pending` - `documented_date: <today>` - `tags: []` 2. **Date format** — Convert dates to ISO 8601 3. **Missing GRADE** — Add `grade_rating: null` placeholder Write corrections in place and re-run lint to verify fixes. ## Integration Points | Component | Relationship | |-----------|-------------| | `aiwg lint` | Underlying CLI command this skill wraps | | `corpus-health` | Lint results feed into health scoring | | `induct-research` | Post-induction hook can trigger lint on new notes | | `ralph` loops | Lint pass as completion gate | | CI/CD | `aiwg lint --ci --ruleset research --fail-on error` | ## Examples ```bash # Full corpus lint /research-lint # Quick summary /research-lint --format summary # CI mode (exit code) /research-lint --ci --fail-on warn # Lint specific directory /research-lint .aiwg/research/findings/ # Auto-fix what's fixable /research-lint --fix # JSON output for programmatic use /research-lint --format json ``` ## References - @$AIWG_ROOT/agentic/code/frameworks/research-complete/lint/ruleset.yaml - @$AIWG_ROOT/src/lint/cli.ts - @$AIWG_ROOT/src/lint/runner.ts
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