Borrowing it
Nothing to install: this file belongs to dfridkin/clawops. 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/dfridkin/clawops/main/.claude/skills/audit-egress/SKILL.mdgit clone --depth 1 https://github.com/dfridkin/clawopsWrote 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/dfridkin/clawops/audit-egress)<a href="https://agentmods.dev/skills/dfridkin/clawops/audit-egress"><img src="https://agentmods.dev/badge/skills/dfridkin/clawops/audit-egress/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/dfridkin/clawops/audit-egress"><img src="https://agentmods.dev/badge/skills/dfridkin/clawops/audit-egress.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 | $0.00000 | $0.00270 |
| Opus 5 | $0.00000 | $0.00135 |
| Sonnet 5 | $0.00000 | $0.00054 |
| Haiku 4.5 | $0.00000 | $0.00027 |
Grade A, and why
audit-egress 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 8d 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
/audit-egress
Audit all outbound network calls in a source file or module.
Steps
-
Scan for outbound calls in the target file(s):
fetch(,axios.,http.request(,https.request(ssh2connect(calls- AWS SDK, GCP SDK, Azure SDK client instantiation
- Pulumi provider resource creation
-
For each call, verify:
- It goes through an AbortSignal (R13)
- Credentials come from
process.env, not function arguments (R6) - The call is documented in the file's module header
-
Check MCP tools additionally:
- Does the tool set
openWorldHint: trueif it makes external calls? - Is the output trimmed to 8KB before returning (R14)?
- Does the tool set
-
Report findings as a structured list:
[PASS] src/transport/ssh.ts:42 — AbortSignal present ✓ [FAIL] src/providers/aws/index.ts:17 — missing AbortSignal
When to run
- Before submitting a PR that adds network calls
- When the
/add-provideror/mcp-toolskill is used - During security review
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.
- 8d ago First seen · 33 lines · 0 tokens per session scan A f1a9983fa049
audit-egress is a skill published in the GitHub repository dfridkin/clawops (2 stars, last pushed today), licensed MPL-2.0. It costs nothing until one of its globs matches a file; then it loads 270 tokens. 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…