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/microwind/ai-skills/request-debuggernpx skills add microwind/ai-skills --skill request-debuggergit clone --depth 1 https://github.com/microwind/ai-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/microwind/ai-skills/request-debugger)<a href="https://agentmods.dev/skills/microwind/ai-skills/request-debugger"><img src="https://agentmods.dev/badge/skills/microwind/ai-skills/request-debugger.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 | $0.00040 | $0.05024 |
| Opus 5 | $0.00020 | $0.02512 |
| Sonnet 5 | $0.00008 | $0.01005 |
| Haiku 4.5 | $0.00004 | $0.00502 |
Grade B, and why
HTTP请求调试器 scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl += ` -d '${data}'`; Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- curl命令测试 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 ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 700 lines · 40 tokens per session scan B 8e7a3d1f125f
HTTP请求调试器 is a skill published in the GitHub repository microwind/ai-skills (75 stars, last pushed 3mo ago), with no licence file. It adds 40 tokens to every session and 5,024 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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noosphere-memory-hermes
Set up and use the Noosphere memory provider in Hermes Agent. Use when a user gives Hermes a Noosphere API key, asks to connect Hermes to Noosphere, configure durable memory, verify the provider, or troubleshoot Hermes Noosphere memory setup.
noosphere
Use this skill when Hermes has the Noosphere memory provider enabled and the task needs durable recall or memory storage.
playwright-best-practices
Use when writing Playwright tests, fixing flaky tests, debugging failures, implementing Page Object Model, configuring CI/CD, optimizing performance, mocking APIs, handling authentication or OAuth, testing accessibility (axe-core), file uploads/downloads, date/time mocking, WebSockets, geolocation, permissions…
tcx-calculation
Run reproducible financial calculations from governed Dataset slices or declared private inputs, reuse exact prior results, and bind decision-relevant metrics to recorded Calculation Runs. Use for returns, risk, valuation, regression, optimization, scenario, or portfolio math that can affect an investment artifact.
product-requirements-doc
Optional PRD methodology — loaded by the questioner agent when a feature request is vague or complex enough to warrant a structured product spec alongside task.md. Produces a PRD artifact that downstream design-author work can ground decisions in.