| name | core |
| version | 0.12.0 |
| description | Canonical skillkit workflow served by the installed CLI. Read before auditing skill packs or analyzing skill usage, context cost, conflicts, coverage, and token burn. |
skillkit core
Skillkit is a local-first observability and structural-audit CLI for AI agent skills. It reads local skill directories and agent session stores. It does not require an account or send telemetry.
Choose the command
- Audit an uninstalled skill, subset, or repository:
skillkit audit <path>
- See which installed skills are used:
skillkit stats
- Check installed-skill and database health:
skillkit health
- Measure always-loaded context and MCP schemas:
skillkit context --mcp
- Compare context before and after installing a pack:
skillkit context --save-baseline <name>, then skillkit context --compare <name>
- Measure observed dead weight for one skill:
skillkit coverage <skill-path>
- Find overlapping triggers:
skillkit conflicts
- Trace one invocation:
skillkit trace <prompt>
- Inspect subscription token burn:
skillkit burn
- Remove unused skills: run
skillkit prune first, then add --yes only when deletion is intended
Audit a skill pack
Use audit for static analysis that does not depend on installation or session history:
skillkit audit ./skills
skillkit audit ./skills/testing ./skills/release
skillkit audit ./skills --include "rn-*"
skillkit audit ./skills --json --strict
The report separates three context layers:
- Catalog cost:
name and description, available during discovery
- Activation cost: the selected
SKILL.md
- On-demand cost: files under
references/
It checks metadata, estimated tokens, line count, bundled references, scripts and assets, broken or unsafe pointers, unreferenced files, explicit reference-routing instructions, duplicate names, and similar descriptions.
--strict exits with status 1 when warnings or errors are present. Token counts are local estimates based on character length, so treat them as consistent budget signals rather than provider-exact billing values.
Usage and context workflow
On a new installation, scan before interpreting usage:
skillkit scan
skillkit stats --all --days 90
skillkit health
Before adding a large skill pack or MCP server:
skillkit context --save-baseline before
skillkit context --mcp
skillkit context --mcp --compare before
Use coverage only when observed traces matter. Use audit for filesystem structure and best-practice conformance.
Automation
Add --json when the command supports machine-readable output. Use audit --json --strict in CI. Agent filters such as --claude, --codex, --cursor, --gemini, and --opencode narrow commands that read installed skills or sessions.
Do not treat unmeasured MCP servers as zero cost. Do not run prune --yes unless deletion is explicitly intended.
Read references/commands.md when exact flags, aliases, JSON behavior, data locations, or the full command catalog are needed. The same reference is included by skillkit skills get core --full.
