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/umarhassankhan929/react-profiler-mcp/speckit-git-validatenpx skills add UmarHassanKhan929/react-profiler-mcp --skill speckit-git-validategit clone --depth 1 https://github.com/UmarHassanKhan929/react-profiler-mcpWrote 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/umarhassankhan929/react-profiler-mcp/speckit-git-validate)<a href="https://agentmods.dev/skills/umarhassankhan929/react-profiler-mcp/speckit-git-validate"><img src="https://agentmods.dev/badge/skills/umarhassankhan929/react-profiler-mcp/speckit-git-validate.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00016 | $0.00492 |
| Opus 5 | $0.00008 | $0.00246 |
| Sonnet 5 | $0.00003 | $0.00098 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
speckit-git-validate 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 5d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago First seen · 54 lines · 16 tokens per session scan A ab7656044903
speckit-git-validate is a skill published in the GitHub repository UmarHassanKhan929/react-profiler-mcp (3 stars, last pushed 4mo ago), with no licence file. It adds 16 tokens to every session and 492 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 2026-08-31.
Other skills, from other repositories
postgresql-expert
Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations.
manage-mcp
Manage MCP servers in Nuxt with @nuxtjs/mcp-toolkit — setup, create tools/resources/prompts, organize with handlers, build interactive MCP Apps, add elicitation/logging/sessions, review, and troubleshoot.
deepsec
Drive the oma-deepsec skill end-to-end. Installs .deepsec/, calibrates cost, runs the right scan/process/triage/revalidate/export pass, gates PRs with process --diff, writes custom matchers, and routes findings to follow-up specialists.
deepinit
Initialize project harness with AGENTS.md as table of contents, ARCHITECTURE.md as domain map, and a structured docs/ knowledge base.
orchestrate
Automated CLI-based parallel agent execution that spawns subagents via Gemini CLI, coordinates through MCP Memory, monitors progress, and runs verification.
plan
PM planning workflow that gathers requirements, decomposes them into prioritized tasks, defines API contracts, and produces both a machine-readable plan and a human-readable tracker in docs/plans/.