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/firstbatchxyz/watchmen/briefnpx skills add firstbatchxyz/watchmen --skill briefgit clone --depth 1 https://github.com/firstbatchxyz/watchmenWhat 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 | $0.00031 | $0.00476 |
| Opus 5 | $0.00015 | $0.00238 |
| Sonnet 5 | $0.00006 | $0.00095 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
brief 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 3d 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
Watchmen brief
You are reporting watchmen's latest findings for the user's current workspace. The user invoked you (via /skills brief or $brief) to find out what changed since the last curator run.
Current state for this workspace
The block below contains the JSON state file watchmen wrote at the end of its last curator run for this project. If it says (no state) or (not a tracked project), watchmen has nothing new to report.
!${CLAUDE_PLUGIN_ROOT}/bin/read_state.sh
What to do
-
If the state says
(no state)or(not a tracked project): tell the user there's nothing new and stop. One short sentence. -
Otherwise, summarize in plain English what changed:
- Which skills were added/updated/removed
- Whether AGENTS.md changed
- When this happened (the
tsfield) - Keep it tight — 3-5 lines max. The user will ask for detail if they want it.
-
If
suggested_skillis non-null in the state: ask the user "Want me to load the<skill>skill for this session?" and wait for a yes/no. If yes, instruct them to invoke it (/skills <name>or$<name>) — you can't load it programmatically, only signal. -
Include a closing link to the run's details:
- If
diff_urlis non-null (schema 2+): show that — it points at the side-by-side diff for this exact run, e.g.Diff: http://127.0.0.1:8979/p/kai-agent-new/diff/<sha> - Else fall back to
viewer_url(the project overview page) - One line, link only — no extra commentary.
- If
The read_state.sh call also touches an acknowledgment file, which clears the pending-brief signal for this project. So once you've shown the user this brief, watchmen will stay quiet about this run until the next curator pass.
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.
- 3d ago First seen · 34 lines · 31 tokens per session scan A e5cb0261b0cf
brief is a skill published in the GitHub repository firstbatchxyz/watchmen (295 stars, last pushed 8d ago), licensed MIT. It adds 31 tokens to every session and 476 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 2026-08-30.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
lark-im
飞书即时通讯：收发消息和管理群聊。发送和回复消息、搜索聊天记录、管理群聊成员、上传下载图片和文件、管理表情回复、发送应用内/短信/电话加急、发送和处理交互卡片（Interactive Card）、监听卡片按钮回调（card.action.trigger）。当用户需要发消息、查看或搜索聊天记录、下载聊天中的文件、查看群成员、搜索群、创建群聊或话题群、管理标记数据、管理 Feed 置顶（添加/移除/查询置顶会话）、管理标签数据、处理卡片回调时使用。.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
reflect
Review recent work, find repeated workflow patterns, and suggest reusable skills, agents, commands, config changes, or playbooks. Use when the user asks to learn from past sessions, improve recurring workflows, or identify what should be turned into reusable agent instructions.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
organize-threads
猫猫辅助整理未分类 thread，分析标题和元数据，建议合适的标签。 Use when: 用户说"帮我整理"、"分类 thread"、点击整理按钮。 Not for: 删除/编辑标签本身。 Output: 按 thread 的标签建议列表。.