skillkit core
SkillWeb & browsingCore agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for conten
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the skillkit core skill
What this skill tells your AI
The instructions your AI receives, as published by akarachen/angel-engine in .agents/skills/core/SKILL.md and read by ahel’s review.
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 - Inspect private usage receipts:
skillkit receipts --pending - Read receipts from another Mac in the tailnet:
skillkit receipts --remote user@mac.tailnet.ts.net --all --json - 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>, thenskillkit 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 prunefirst, then add--yesonly 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:
nameanddescription, 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
skillkit receipts --pending
skillkit receipts --remote user@mac.tailnet.ts.net --all --json
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.
Remote receipt collection runs Skillkit beside the source sessions, requires an exact version match, and transfers only private receipt JSON. Do not copy raw remote transcripts or the remote Skillkit database. 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.
Signals
- GitHub stars
- 20
- Forks
- 2
- Last commit
- Sep 2026
Others that do the same job
Advanced
- Catalog kind
- skill
- Gateway key
core- Source
- github.com/akarachen/angel-engine