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 skills add omnigentx/jarvis --skill mcp-authoringgit clone --depth 1 https://github.com/omnigentx/jarvisWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/omnigentx/jarvis/mcp-authoring)<a href="https://agentmods.dev/skills/omnigentx/jarvis/mcp-authoring"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/mcp-authoring.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 157 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 195 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
What 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 5.1 | $0.00080 | $0.03735 |
| Opus 5 | $0.00040 | $0.01868 |
| Sonnet 5 | $0.00016 | $0.00747 |
| Haiku 4.5 | $0.00008 | $0.00374 |
Grade A, and why
mcp-authoring scanned grade A with 1 finding 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 8d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- `eval()`, `exec()`, `os.system()` — use `subprocess.run([...])` instead How it starts
The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP AUTHORING & USAGE
You can extend yourself with new MCP servers via the mcp_admin tools, AND
you can inspect/attach/detach existing ones. Read the matching section below
for the situation in front of you.
Decision tree — pick the section
| Situation | Section |
|---|---|
| "What MCPs do I have? / Show me the catalog" | Discovery |
| "Install jq / add the github MCP / register this URL" — server already exists | Path A |
| "I need a custom tool that doesn't exist anywhere" | Path B |
| "Tool X is broken / silently failing" | Hot-fix then re-verify |
| "Detach this server from agent Y" | mcp_detach_from_agent (one call) |
Discovery — inspect before mutating
Before adding/changing anything, find out what's already there. The right tool depends on what you actually need to know:
| You need… | Call | Cost |
|---|---|---|
| List of catalog server names + transport + who's attached | mcp_list_servers() |
compact (~80 chars/server) |
| Full config of ONE server (command, args, env, cwd) | mcp_get_server(name="…") |
small |
| Full config of EVERY server (rare — usually wrong) | mcp_list_servers(verbose=True) |
heavy (~500 chars/server × N) |
| Live tool list + descriptions for one server | mcp_test_server(name="…") |
spawn subprocess, descriptions auto-trimmed to 240 chars |
| Generated (Path-B) workspace inventory | mcp_list_generated() |
compact (just tool names) |
| Full manifest + history of one generated server | mcp_get_generated(name="…") |
larger |
Default to compact lists. The catalog has ~28 servers; calling the
verbose version pulls ~13 KB into context. Get the names compactly, then
mcp_get_server(name) only the ones you'll actually act on.
Path A vs Path B — never mix
| Situation | Flow |
|---|---|
| Server already exists as an npm/pypi package or a hosted URL | Path A (config-only) |
| You'd need to write the tool code yourself | Path B (scaffold-then-test) |
If you start Path B and then realize an existing package solves the
problem, drop the scaffold (mcp_clean_workspace(scope="<name>")) and
restart in Path A.
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.
- 8d ago First seen · 374 lines · 80 tokens per session scan A 6a339c87afbb
mcp-authoring is a skill published in the GitHub repository omnigentx/jarvis (37 stars, last pushed 12d ago), licensed MIT. It adds 80 tokens to every session and 3,735 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). 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.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…