Borrowing it
Nothing to install: this file belongs to testdino-hq/testdino-mcp. 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/testdino-hq/testdino-mcp/main/.claude/skills/review/SKILL.mdgit clone --depth 1 https://github.com/testdino-hq/testdino-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/testdino-hq/testdino-mcp/review)<a href="https://agentmods.dev/skills/testdino-hq/testdino-mcp/review"><img src="https://agentmods.dev/badge/skills/testdino-hq/testdino-mcp/review/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/testdino-hq/testdino-mcp/review"><img src="https://agentmods.dev/badge/skills/testdino-hq/testdino-mcp/review.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 | $0.00017 | $0.00787 |
| Opus 5.5 | $0.00007 | $0.00315 |
| Sonnet 5.5 | $0.00003 | $0.00157 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
review 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 2mo 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review $ARGUMENTS for bugs, correctness, and convention violations.
If $ARGUMENTS is "staged" or empty, review all staged/unstaged git changes.
Process
- Read CLAUDE.md — load project rules and conventions
- Read the target code — understand before judging
- Check against each category below — report only real issues with file:line references
Categories
MCP Protocol Compliance (highest priority)
- Does the tool return the correct response shape?
{ content: [{ type: "text", text: string }] } - Is
console.logused anywhere? (corrupts stdio — must beconsole.error) - Does the tool name match the routing in
index.ts? - Is the tool registered in both the
toolsarray AND the routing if-blocks? - Does
inputSchemaaccurately describe what the handler expects?
Tool Pattern Consistency
- Does the tool follow the same pattern as existing tools?
- Auth:
getApiKey(args)called first with proper error? - URL: Built via
endpoints.ts, not inline? - Response: Formatted with
JSON.stringify(response, null, 2)? - Error: Wrapped in try/catch with contextual message?
- Types: Consistent use of
String()/Number()for conversions?
Data Integrity
- Can any code path lose the API response silently?
- Are required parameters validated before the API call?
- Could a missing optional param cause the URL to be malformed?
- Are boolean params correctly converted to strings for query params?
Tool Descriptions (critical for AI agent usability)
- Is the tool description specific enough for an AI to choose correctly?
- Does every
inputSchemaproperty have adescription? - Are
enumvalues provided for fields with known options? - Are
requiredfields accurately marked? - Would an AI know when NOT to use this tool based on the description?
Security
- Is the PAT exposed in any error message or response?
- Are user inputs passed to URLs without sanitization?
- Are file paths validated before reading (for attachment tools)?
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.
- 2mo ago First seen · 98 lines · 17 tokens per session scan A 8ffdf415e700
review is a skill published in the GitHub repository testdino-hq/testdino-mcp (10 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 787 once invoked, about $0.0001 per session on Opus 5.5. 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.
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