Borrowing it
Nothing to install: this file belongs to Grinv/anilist-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Grinv/anilist-mcp-server/main/.agents/skills/prompt-check/SKILL.mdgit clone --depth 1 https://github.com/Grinv/anilist-mcp-serverWrote 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/grinv/anilist-mcp-server/prompt-check)<a href="https://agentmods.dev/skills/grinv/anilist-mcp-server/prompt-check"><img src="https://agentmods.dev/badge/skills/grinv/anilist-mcp-server/prompt-check/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/grinv/anilist-mcp-server/prompt-check"><img src="https://agentmods.dev/badge/skills/grinv/anilist-mcp-server/prompt-check.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00053 | $0.00391 |
| Opus 5 | $0.00026 | $0.00196 |
| Sonnet 5 | $0.00011 | $0.00078 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
prompt-check 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 9d 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.
What it actually says
Prompt check — live-test every MCP Prompt argument combination
A static read comparing prompt text against tool names/params misses argument-handling bugs. Actually render every prompt through the real MCP protocol:
npx @modelcontextprotocol/inspector --cli node dist/index.js --method prompts/list
npx @modelcontextprotocol/inspector --cli node dist/index.js --method prompts/get \
--prompt-name <name> --prompt-args key=value key2=value2
--prompt-args takes space-separated key=value pairs, not a JSON blob
— the CLI rejects JSON with "Invalid parameter format".
Run each prompt with:
- No args.
- Only one of several optional args set at a time — an argument that's
individually optional can still have a bug that only shows up when given
alone (e.g. a prompt silently ignoring
yearbecause its branching logic requiredseasonto also be present, even though the two are independent filters on the underlying tool). - All optional args set together.
Then check the rendered plan against what the prompt claims to deliver, not
just that it renders: would running those exact tool calls actually produce
it? A plan that omits a needed sort/filter can read fine and still be
wrong (confirmed: hidden_gems told the model to pick underrated titles out
of a sort-less search_media call, i.e. AniList's default id order).
Read-only, no-account-risk — never route this through anything that touches mutations.
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.
- 9d ago First seen · 39 lines · 53 tokens per session scan A 3473f41171be
prompt-check is a skill published in the GitHub repository Grinv/anilist-mcp-server (1 stars, last pushed 16d ago), licensed MIT. It adds 53 tokens to every session and 391 once invoked, about $0.0003 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
ai-observability-promptfoo
Testing and evaluation framework for LLM prompts and applications -- promptfooconfig.yaml, assertions, model-graded evals, red teaming, CI/CD integration, custom providers, and comparative evaluation.
recipe-eval-prompt
Compares original and optimized prompts through repeated blind paired execution in git worktrees. Use when evaluating prompt improvement effects or learning prompt engineering through concrete examples.
prompt-testing
Use this skill when you need to test prompt behavior, regression risk, and output boundaries across versions; triggers include prompt testing.
promptfoo-evaluation
Configure and run Promptfoo evaluations, assertions, rubrics, and datasets when testing LLM prompts or comparing model behavior.
api-testing
Testing patterns for MCP tool/resource handlers using createMockContext and Vitest. Covers mock context options, handler testing, McpError assertions, format testing, Vitest config setup, and test isolation conventions.
field-test
Exercise tools, resources, and prompts against a live HTTP server via MCP JSON-RPC over curl. Starts the server, surfaces the catalog, runs real and adversarial inputs, and produces a tight report with concrete findings and numbered follow-up options. Use after adding or modifying definitions, or when the user asks to…