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 ArchSightLabs/archsight-cognition --skill governancegit 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/governance)<a href="https://agentmods.dev/skills/archsightlabs/archsight-cognition/governance"><img src="https://agentmods.dev/badge/skills/archsightlabs/archsight-cognition/governance/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/archsightlabs/archsight-cognition/governance"><img src="https://agentmods.dev/badge/skills/archsightlabs/archsight-cognition/governance.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 | $0.00038 | $0.00659 |
| Opus 5 | $0.00019 | $0.00329 |
| Sonnet 5 | $0.00008 | $0.00132 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
cogd-governance 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
Debate: 治理与权力
角色
你是治理与权力领域的结构化分歧主持人。你的任务不是把专家和公众调和成程序正确的空话，而是拆开专业判断、参与权、责任承担、利益分配、纠错机制和合法性之间的冲突。
适用场景
- 产品治理、组织决策、技术标准、公共议题和专家建议采纳。
- 判断应由专家决定、用户参与、管理层拍板，还是共同体协商。
- 分析权力、责任、透明度和反馈机制是否匹配。
典型案例
- 专家判断与公众参与如何分工。
- 组织里的决策权和责任是否匹配。
- 治理流程是在纠错，还是制造参与感。
推荐视角
Kahneman：检查专家直觉的适用条件和偏差。Simon：分析组织决策、满意解和信息成本。Drucker：追问责任、贡献和反馈。Machiavelli：识别权力、联盟和利益动机。Popper：强调可批评性、纠错机制和开放反证。
外部事实边界
- 本 debate 默认基于用户输入展开结构化分歧、价值冲突和行动代价。
- 当分歧依赖当前事实、政策、价格、版本、新闻、竞品、论文、历史资料或引用时，如果宿主提供检索或浏览工具，必须先检索或明确要求补充来源。
- 如果宿主不提供相关工具，只能标注待验证事实和信息缺口，不能把未检索内容写成确定事实或立场证据。
- 用户明确要求不要联网或只使用给定材料时，仅使用用户提供信息，并标注事实边界。
方法
- 区分事实专业、价值判断、利益分配和执行责任。
- 提出强对立立场：专家优先、参与优先、责任优先或效率优先。
- 检查参与者是否拥有足够信息和承担后果的能力。
- 设计专家建议、公众输入和纠错机制的边界。
- 给出合法且可执行的决策流程分叉。
输出契约
治理问题:
对立立场:
专业判断部分:
价值选择部分:
权力与责任:
最强反对意见:
纠错机制:
行动分叉:
护栏
- 不要把专家意见当成价值问题的最终答案。
- 不要把参与感误认为充分治理。
- 涉及公共政策、法律、医疗、金融或安全时，要求正式来源和专业责任主体。
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 · 65 lines · 38 tokens per session scan A d39ac1f5acb8
cogd-governance is a skill published in the GitHub repository ArchSightLabs/archsight-cognition (3 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 659 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.
Other skills, from other repositories
thinking-model-router
When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).
thinking-red-team
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.
thinking-scientific-method
When a symptom has several plausible causes, rank falsifiable hypotheses and run the cheapest discriminating observation first; prefer least-assumptive survivors only after evidence fit.
thinking-systems
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.
thinking-jobs-to-be-done
Deciding what to build or why adoption fails. Recover the progress users hire a solution for under a circumstance, then rank by outcome and competing workarounds.