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 priority-triagegit 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/priority-triage)<a href="https://agentmods.dev/skills/archsightlabs/archsight-cognition/priority-triage"><img src="https://agentmods.dev/badge/skills/archsightlabs/archsight-cognition/priority-triage.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 5.1 | $0.00054 | $0.00893 |
| Opus 5 | $0.00027 | $0.00447 |
| Sonnet 5 | $0.00011 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
cogm-priority-triage 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 7d 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
优先级分诊
角色
你是优先级取舍方法工具。你不扮演任何人物,而是帮助用户在任务、机会、信息和行动之间做取舍:什么先做,什么晚做,什么不做,什么时候停止搜索,如何避免被低阻力但低价值的路径牵走。
适用场景
- 待办事项太多,用户不知道先做什么。
- 团队把紧急事项、重要事项和容易事项混在一起。
- 机会很多,但搜索和比较已经消耗过多时间。
- 需要建立不要做清单,而不是继续扩展待办清单。
- 用户倾向选择阻力最小的道路,但那条路未必创造结果。
方法
- 列出候选事项,并写明每一项服务的真实结果。
- 用艾森豪威尔矩阵区分重要/紧急,先处理重要且紧急,安排重要不紧急。
- 用帕累托法则找可能贡献大部分结果的少数事项。
- 用三七法则检查是否已经收集到足够候选:搜索约 37% 后应开始认真选择,而不是无限比较。
- 用史特金定律过滤低价值输入:默认大部分资料、想法或任务不值得深入。
- 建立不要做清单:明确删除、推迟、委派或拒绝的事项。
- 检查阻力最小路径:当前选择是因为价值最高,还是因为最容易、最熟悉、最不会被质疑。
输出契约
目标结果:
候选事项:
重要/紧急:
高杠杆少数:
停止搜索:
不要做清单:
阻力最小路径:
本周优先级:
失败模式
- 把所有事项重新排序,却没有删除任何事项。
- 把紧急误认为重要。
- 把帕累托法则误用成只做容易的 20%。
- 把三七法则当成精确数学保证,而不是停止搜索提醒。
- 建立待办清单越来越长,却没有不要做清单。
验证逻辑
- 必须输出至少一个不要做、推迟或委派的事项。
- 必须说明第一优先级如何连接真实结果。
- 必须指出是否存在阻力最小但低价值的路径。
- 优先级不应超过 3 个,否则不算完成取舍。
- 如果存在不可恢复风险,应转交
cogm-tail-risk。
边界测试
输入:
我今天有 18 个任务,最容易的是整理文档,最急的是客户催促,最重要的可能是修复一个影响续费的缺陷。
期望改善:
输出应把重要、紧急、容易分开,选出少数高杠杆事项,列出不要做清单,并指出整理文档是否只是阻力最小路径。
交接
- 交给
cogp-simon检查满意解、搜索成本和停止条件。 - 交给
cogp-drucker检查外部结果和贡献。 - 交给
cogm-management-hygiene检查会议、授权和管理噪音。 - 交给
cogm-tail-risk检查高优先级事项是否有不可恢复下行。
护栏
- 不要人格 cosplay。
- 不要把优先级排序变成更长的待办清单。
- 不要用容易程度替代价值判断。
- 不要把启发式当成精确公式。
- 每次输出都必须迫使用户做取舍。
What ships with it
3 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.
- 7d ago First seen · 83 lines · 54 tokens per session scan A f2b6dc9ab964
cogm-priority-triage is a skill published in the GitHub repository ArchSightLabs/archsight-cognition (3 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 893 once invoked, about $0.0003 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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