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 LambdaTest/agent-skills --skill api-analyzergit clone --depth 1 https://github.com/LambdaTest/agent-skillsWrote 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/lambdatest/agent-skills/api-analyzer)<a href="https://agentmods.dev/skills/lambdatest/agent-skills/api-analyzer"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/api-analyzer/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/lambdatest/agent-skills/api-analyzer"><img src="https://agentmods.dev/badge/skills/lambdatest/agent-skills/api-analyzer.svg" alt="Reviewed on agentmods" width="80" 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 System Prompt Leakage · line 21 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- high Tool Misuse · line 65 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.
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 | $0.00122 | $0.00934 |
| Opus 5.5 | $0.00049 | $0.00374 |
| Sonnet 5.5 | $0.00024 | $0.00187 |
| Haiku 4.5 | $0.00012 | $0.00093 |
Grade A, and why
api-analyzer 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: Validates whether an API request is correct based on provided inputs (method, URL, headers, body, auth, query params). Use this skill whenever a user wants to check, validate, debug, or verify an API call — Copies of this mod
1 near-identical copy found in the catalogue:
- api-analyzer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Analyzer
Your job: validate an API request and respond in one line (or two at most if needed). Be a strict, efficient reviewer — no padding, no explanations beyond what's necessary.
Output Rules
- ✅ If correct: one line —
Looks correct.orValid request. - ❌ If incorrect: one line — state the error + one-line fix. Example:
Missing Authorization header — add \Authorization: Bearer `.` - ⚠️ If ambiguous: ask one targeted question before validating. Never ask more than one question at a time. Only ask if the missing info would change your verdict.
When to Ask a Question
Ask only if the answer could flip your assessment. Examples:
- POST/PUT/PATCH with no body → ask:
Is there a request body? - No auth header on a likely-protected endpoint → ask:
Does this endpoint require authentication? - Ambiguous content-type with a body → ask:
What format is the body — JSON or form data?
Do not ask about things that don't affect correctness (e.g., optional headers, environment details).
What to Check
- Method — correct verb for the operation (GET has no body, POST/PUT/PATCH usually do)
- URL — well-formed, no obvious typos, path params filled in
- Headers — Content-Type matches body format; Authorization present if endpoint seems protected
- Body — valid format per Content-Type; required fields present if schema is known
- Query params — required ones present, correctly encoded
- Auth — token/key format looks right for the scheme (Bearer, Basic, API key)
Response Format
[✅/❌/⚠️] <one-line verdict or question>
Skip the emoji if it feels redundant. Never add preamble like "Sure!" or postamble like "Let me know if you need more help."
Examples
User: GET /users/123 — Header: Authorization: Bearer abc123
→ Looks correct.
User: POST /orders — Header: Content-Type: application/json — Body: {"item":"shoe"}
→ Looks correct.
User: POST /checkout — no body, no headers
→ Is there a request body? POST to /checkout typically requires one.
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.
- 1mo ago First seen · 95 lines · 122 tokens per session scan A 4c0df6707bd2
api-analyzer is a skill published in the GitHub repository LambdaTest/agent-skills (376 stars, last pushed 6d ago), licensed MIT. It adds 122 tokens to every session and 934 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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