Create feature catalog

Skill kunalsuri/ai-fication-kit/.claude/skills/create-feature-catalog

AI-Fication Kit: A Simple & Elegant Way for Making any Codebase AI-native through Scaffolded, Human-verified Context and Development Loop.

Install

npx -y skills add kunalsuri/ai-fication-kit --skill create-feature-catalog

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Deep-mine the source code to discover implemented features; writes ai/analysis/FEATURE_CATALOG.md.

SKILL.md

1.4 KB, as published. Nobody here has run it

Build the feature catalog — the highest-value artifact for agents. Budget significant exploration; use repo-explorer for the heavy reading.

Method

Start from user-visible surfaces: routes, UI entry points, CLI commands, public APIs. Each surface is a candidate feature.
For each feature, trace the touch list across layers: UI, backend/services, persistence (tables/collections/files), and tests that exercise it.
Cluster and name features the way a USER would name them, not by module names.

Output — `ai/analysis/FEATURE_CATALOG.md`

For every feature: name · business goal (one line) · touch list per layer · verifying tests · related features. End with two sections agents use most:

"Where new code lives" — a decision tree from feature-type to target directories.
The 3-file rule — for each feature, the 3 files to read first to understand it.

Rules

Every entry [inferred]. Where a layer can't be confirmed, write "UNSURE".
Do not modify source. Update ai/guide/FEATURE_MAP.md candidate list to reference the catalog, nothing more.
Print a sampling guide at the end: the 5 entries a human should spot-check first (pick the ones you are least sure of).