ninja-enrich
Enrich meta.yaml long_description fields from man pages and websites
Best use case
ninja-enrich is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Enrich meta.yaml long_description fields from man pages and websites
Teams using ninja-enrich 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/ninja-enrich/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ninja-enrich Compares
| Feature / Agent | ninja-enrich | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Enrich meta.yaml long_description fields from man pages and websites
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.
SKILL.md Source
# Ninja Enrich Populate `long_description` fields in `meta.yaml` files by fetching content from man pages, website meta descriptions, or `--help` output. **Usage:** `/ninja-enrich` or `/ninja-enrich --force` ## Execution Run the enrich script: ```bash .claude/scripts/ninja-enrich.sh $ARGUMENTS ``` ## Sources (tried in order per tool) 1. **Man page** — `man -P cat <binary>` → parse `NAME` section 2. **Website** — fetch `website:` URL → extract `<meta description>` or `og:description` 3. **--help** — `<binary> --help` → first meaningful output line 4. **Skip** — no source available ## Flags | Flag | Effect | |------|--------| | `--force` | Re-fetch even if `long_description` already set | | `--path mainmenu/network` | Limit enrichment to a subtree | | `--dry-run` | Show what would change without writing files | ## What it updates - `long_description:` field in each `*.meta.yaml` / `meta.yaml` (source of truth) - SQLite cache (`.cache/menu.db`) rebuilt automatically after YAML updates ## When to use - After adding new scripts that have man pages - After adding `website:` fields to web-app meta files - Periodically to refresh descriptions as upstream docs change (use `--force`) - With `--dry-run` to preview changes before committing
Related Skills
known-motif-enrichment
This skill should be used when users need to perform known motif enrichment analysis on ChIP-seq, ATAC-seq, or other genomic peak files using HOMER (Hypergeometric Optimization of Motif EnRichment). It identifies enrichment of known transcription factor binding motifs from established databases in genomic regions.
functional-enrichment
Perform GO and KEGG functional enrichment using HOMER from genomic regions (BED/narrowPeak/broadPeak) or gene lists, and produce R-based barplot/dotplot visualizations. Use this skill when you want to perform GO and KEGG functional enrichment using HOMER from genomic regions or just want to link genomic region to genes.
parallel-data-enrichment
Structured company and entity data enrichment using Parallel AI Task API with core/base processors. Returns typed JSON output. No binary install — requires PARALLEL_API_KEY in .env.local.
Sales Lead Enrichment
Enrich a lead or company with deep research using parallel AI agents, web scraping, and data integrations (Apollo, AI Ark, Apify). Use when someone wants to research a lead, enrich a contact, look up a company, find intel on a prospect, score a lead, or build a prospect profile. Returns a complete intelligence profile with company overview, person background, buying signals, lead score, and recommended outreach approach. Do NOT use for writing emails, proposals, or outreach -- use sales-sequence or proposal for those.
data-governance-enrichment
Enrich CRM data: tools, waterfall approach, automation, quality control. Use when designing or improving data enrichment in rev ops.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
nosql-expert
Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.
nosql-databases
Apply NoSQL best practices for MongoDB, Convex, and document databases. Use when designing schemas, writing queries, optimizing performance, or building applications with non-relational databases. Use with database-expert for query optimization and DBA-level tuning (20+ years experience).
nodejs-javascript-vitest
Guidelines for writing Node.js and JavaScript code with Vitest testing Triggers on: **/*.js, **/*.mjs, **/*.cjs
nodejs-best-practices
Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.
nodejs-backend-typescript
Node.js backend development with TypeScript, Express/Fastify servers, routing, middleware, and database integration
nodejs-backend-patterns
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.