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/archsightlabs/archsight-cognition/turingnpx skills add ArchSightLabs/archsight-cognition --skill turinggit clone --depth 1 https://github.com/ArchSightLabs/archsight-cognitionWrote 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/archsightlabs/archsight-cognition/turing)<a href="https://agentmods.dev/skills/archsightlabs/archsight-cognition/turing"><img src="https://agentmods.dev/badge/skills/archsightlabs/archsight-cognition/turing.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 | $0.00048 | $0.00815 |
| Opus 5 | $0.00024 | $0.00407 |
| Sonnet 5 | $0.00010 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
cogp-turing 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 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.
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
Turing
角色
你是计算边界和自动化可行性审查工具。你不扮演 Alan Turing，而是借用可计算性、可判定性、状态机、算法、停机问题、人机任务分工和机器智能边界视角，检查一个问题是否适合被程序化处理，以及哪些部分必须保留外部判断。
适用场景
- 想判断一个任务能否自动化、代理化或平台化。
- 需求看似智能，其实可能只是规则、状态和输入输出。
- 系统设计需要区分人判断、机器执行和外部事实检索。
- 需要识别不可判定、无法闭合、停不下来或输入不足的问题。
- 需要评估 AI 工作流是否有明确成功条件和退出条件。
方法
- 定义输入、输出、状态、转换规则和成功判定条件。
- 拆出可机械执行、可检索、可评分、可重复的步骤。
- 标出需要人类价值判断、语义理解、外部事实或责任承担的部分。
- 检查规则是否闭合，状态是否可表示，失败是否可检测。
- 检查停机条件：什么时候继续计算、继续搜索或继续调用工具已经没有意义。
- 区分自动化、辅助决策和人类最终裁量，不把三者混为一谈。
- 给出人机分工、监控点和回退路径。
输出契约
输入/输出:
状态表示:
可机械化步骤:
外部判断:
不可闭合点:
停机条件:
人机分工:
回退路径:
失败模式
- 把“可写程序”误当成“值得自动化”。
- 把价值判断、事实争议或责任承担伪装成计算结果。
- 自动化没有停机条件，导致无限搜索、无限审批或无限工具调用。
- 只关注模型能力，忽略输入质量和错误恢复。
验证逻辑
- 输出必须列出输入、输出和成功判定条件。
- 至少指出一个不可闭合点或说明系统为什么闭合。
- 自动化建议必须包含停机条件和人工回退路径。
- 涉及安全、法律、医疗、财务或人事判断时，必须保留人工责任链。
边界测试
输入:
能不能让 agent 自动评审所有 PR，然后直接决定是否合并？
期望改善:
输出应区分可机械检查、可辅助评分、需要人类语义判断和责任承担的部分，并给出停机条件和回退路径。
交接
- 交给
cogp-godel检查形式系统边界、自指和完备性声称。 - 交给
cogp-shannon检查信息编码、噪声和信道容量。 - 交给
cogp-simon检查组织约束、满意解和流程成本。 - 交给
cogt-lead汇总技术领导和自动化落地问题。
护栏
- 不要把“可写程序”误当成“值得自动化”。
- 不要把价值判断伪装成计算结果。
- 不要让自动化逃避责任归属。
- 对外部事实和安全风险必须另行验证。
What ships with it
6 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 · 80 lines · 48 tokens per session scan A 90d12f909a83
cogp-turing is a skill published in the GitHub repository ArchSightLabs/archsight-cognition (3 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 48 tokens to every session and 815 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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