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 unknowbug/anchorlaw --skill anchor-noisegit clone --depth 1 https://github.com/unknowbug/anchorlawWrote 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/unknowbug/anchorlaw/anchor-noise)<a href="https://agentmods.dev/skills/unknowbug/anchorlaw/anchor-noise"><img src="https://agentmods.dev/badge/skills/unknowbug/anchorlaw/anchor-noise/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/unknowbug/anchorlaw/anchor-noise"><img src="https://agentmods.dev/badge/skills/unknowbug/anchorlaw/anchor-noise.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 | $0.00040 | $0.00506 |
| Opus 5 | $0.00020 | $0.00253 |
| Sonnet 5 | $0.00008 | $0.00101 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
anchor-noise 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 6d 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
anchor.noise — 噪声卡管理
Protocol: spec/protocol-v0.20.md §3 (Noise Card JSON Schema) Layer: L3 (Noise) Execution: inline
触发场景
运行时观察到失败/异常；或存在未解决噪声卡积压时。
操作步骤
- 创建（§14.4 唯一代码内钩子，无 CLI 入口）——在捕获失败的
except块中调用：
必填字段：import anchorlaw as pract # 需已安装 anchorlaw（stub 仅含 test/idk） try: result = func(bad_input) except Exception as e: pract.create_noise_card( trigger="func(bad_input)", function_name="func", observed=f"抛出 {type(e).__name__}: {e}", expected="应返回默认值而非崩溃", discovery="函数未处理该输入形态", curriculum="处理外部输入时先校验形态，再执行运算", ) raisenoise_id(自动) /timestamp(自动) /trigger/function_name/observed/expected（§3 schema）。 - 列出：
anchorlaw noise list（--all含已解决） - 搜索：
anchorlaw noise search <keyword> - 解决（转为回归测试）：
anchorlaw noise resolve <noise_id> --converted-test "<测试描述>"
输出
创建的噪声卡 / 积压清单 / 搜索命中 / 解决记录。
约束
curriculum必须可操作（可复用教训），不写空话。- 除创建外的所有管理操作一律 CLI（§14.4）。
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.
- 6d ago Changed 29cfa2ac6e4a
- 10d ago First seen · 48 lines · 40 tokens per session scan A 17afe5af2b01
anchor-noise is a skill published in the GitHub repository unknowbug/anchorlaw (5 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 506 once invoked, about $0.0002 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.
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