Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/olaservo/skilljack-mcp/skilljack-docsnpx skills add olaservo/skilljack-mcp --skill skilljack-docsgit clone --depth 1 https://github.com/olaservo/skilljack-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00026 | $0.05630 |
| Opus 5 | $0.00013 | $0.02815 |
| Sonnet 5 | $0.00005 | $0.01126 |
| Haiku 4.5 | $0.00003 | $0.00563 |
Grade A, and why
skilljack-docs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skilljack MCP Documentation
An MCP server that jacks Agent Skills directly into your LLM's brain.
Recommended: For best results, use an MCP client that supports
tools/listChangednotifications (e.g., Claude Code). This enables dynamic skill discovery - when skills are added or modified, the client automatically refreshes its understanding of available skills. Alternatively, use--staticmode for predictable behavior with a fixed skill set.
Tool search / deferred tools. By default, skilljack delivers its skill catalog via MCP server instructions, which arrive in the
initializehandshake and reach the model even when tool search / deferred tool loading is enabled (the default on modern Claude Code, ~2.1.x) — automatic skill activation works out of the box. The legacy--catalog=tool-descriptionmode (not recommended) delivers the catalog inside theload-skilltool description instead, but tool-search clients defer MCP tool descriptions out of context, so that mode requires disabling tool search (e.g.ENABLE_TOOL_SEARCH=false) for auto-activation. See Catalog Delivery.
Features
- Dynamic Skill Discovery - Watches skill directories and automatically refreshes when skills change
- Multiple Sources - Local directories, GitHub repositories, and
.well-known/agent-skills/publishers (both allowlisted) - Tool List Changed Notifications - Sends
tools/listChangedso clients can refresh available skills load-skillTool - Load full skill content on demand (progressive disclosure)- MCP Prompts - Load skills via
/skillprompt with auto-completion or per-skill prompts - MCP Resources - Access skills via
skill://URIs aligned with SEP-2640 - Resource Subscriptions - Real-time file watching with
notifications/resources/updated - Configuration UI - Manage skill directories through an interactive UI in supported clients
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 488 lines · 26 tokens per session scan A 2eb52964709c
skilljack-docs is a skill published in the GitHub repository olaservo/skilljack-mcp (16 stars, last pushed 11d ago), licensed MIT. It adds 26 tokens to every session and 5,630 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…