Agent skill · Frontend

mapping-features

Generate behavioral/feature documentation for web apps using code-first analysis. Reads source code and _MAP.md files to produce _FEATURES.md, with optional visual verification via browser automation. Companion to mapping-codebases. Use when documenting app behavior, creating feature inventories, generating behavioral ground truth for agents, or before modifying UI code. Triggers on "map features", "document app behavior", "feature inventory", "what does this app do".

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill mapping-features --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Version: 0.3.0
Path: skills/analysis/mapping-features/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Mapping Features Generate `_FEATURES.md` files documenting what a web app *does* — screens, flows, states, behavioral invariants. Companion to `mapping-codebases` which documents code *structure*. **v0.3.0: Code-first architecture.** The code IS the ground truth; screenshots are supplementary verification. ## Prerequisites 1. **mapping-codebases** must have run first (`_MAP.md` files exist) 2. **Claude API key** available (via `api-credentials` skill or `ANTHROPIC_API_KEY` env var) 3. *Optional:* **webctl** for visual verification (not required for `--code-only`) ## Usage ```bash # Code-only analysis (no browser needed): python /mnt/skills/user/mapping-features/scripts/featuremap.py \ --app-url https://example.com --codebase /path/to/repo --code-only # Full pipeline (code analysis + selective visual verification): python /mnt/skills/user/mapping-features/scripts/featuremap.py \ --app-url https://example.com --codebase /path/to/repo # Incremental update: python /mnt/skills/user/mapping-features/scripts/featuremap.py \ --app-url https://example.com --codebase . --incremental ``` ### Options | Flag | Default | Description | |------|---------|-------------| | `--app-url` | required |

What's inside
Steps it walks through
  1. Prerequisites
  2. Usage
  3. Options
  4. Architecture: Code-First Pipeline
  5. Phase 1: DISCOVER
  6. Phase 2: ANALYZE
  7. Phase 3: VERIFY (optional)
  8. Phase 4: ASSEMBLE
  9. Environment-Adaptive Batching
  10. Incremental Mode
  11. Auth / Gated Pages
  12. Output Format
  13. Relationship to CLAUDE.md
  14. Limitations
Ships with 1 file
  • metadata.json
Commands it runs
Code-only analysis (no browser needed):
python /mnt/skills/user/mapping-features/scripts/featuremap.py \
Full pipeline (code analysis + selective visual verification):
Incremental update:
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About this skill
What does the mapping-features skill do?

Generate behavioral/feature documentation for web apps using code-first analysis. Reads source code and _MAP.md files to produce _FEATURES.md, with optional visual verification via browser automation. Companion to mapping-codebases. Use when documenting app behavior, creating feature inventories, generating behavioral ground truth for agents, or before modifying UI code. Triggers on "map features", "document app behavior", "feature inventory", "what does this app do".

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill mapping-features --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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