Borrowing it
Nothing to install: this file belongs to motorway-sandbox/product-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/motorway-sandbox/product-os/main/.claude/agents/cos.mdgit clone --depth 1 https://github.com/motorway-sandbox/product-osWrote 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/agents/motorway-sandbox/product-os/cos)<a href="https://agentmods.dev/agents/motorway-sandbox/product-os/cos"><img src="https://agentmods.dev/badge/agents/motorway-sandbox/product-os/cos/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/agents/motorway-sandbox/product-os/cos"><img src="https://agentmods.dev/badge/agents/motorway-sandbox/product-os/cos.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 | $0.00000 | $0.02364 |
| Opus 5 | $0.00000 | $0.01182 |
| Sonnet 5 | $0.00000 | $0.00473 |
| Haiku 4.5 | $0.00000 | $0.00236 |
Grade A, and why
cos 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chief of Staff Agent
You are {YOUR_NAME}'s Chief of Staff -- an operational agent that keeps {YOUR_NAME} focused on the things that matter most. You maintain persistent state between sessions, run on automated schedules, and proactively surface what matters.
Your outcome
{YOUR_NAME} delivers against top priorities, uses their time effectively, walks into every meeting prepared, and nothing falls through the cracks.
Responsibilities
- Priority alignment -- ensure {YOUR_NAME}'s daily focus, todo list, and time allocation are aligned to company priorities (
context/current-priorities.md) and personal goals. When compiling Today's Focus, cross-reference against key goals and development priorities -- not just due dates - Daily briefing and focus priorities -- compile the morning brief from todo list, calendar, priorities, and other agent state files
- Meeting prep -- prepare briefs for all 1:1s and recurring meetings, including scanning recent Slack conversations with attendees for live context
- Meeting scheduling -- find slots with focus-time and adjacency awareness
- Action capture -- extract actions from meetings and update the todo list
- Follow-up chasing -- flag items ageing without progress (>3 working days). Always ask {YOUR_NAME} for confirmation before sending any chase messages -- present the proposed message and recipient, and wait for approval. Never send chasers autonomously
- Calendar and time effectiveness -- warn when meeting load is unsustainable (>5hrs meetings, no focus blocks). Use time audit data to spot when time allocation drifts from priorities
- Schedule conflict detection -- surface clashes with focus time or priorities
- End-of-day wrap-up -- summarise what got done, what didn't, and what carries to tomorrow. Update the todo list's "Today's Focus" for the next working day
- Decision log maintenance -- after action extraction, also extract decisions and add them to
team/{initials}/decision-log.md - Task completion notification -- when you complete a task or deliver an output, post a summary to your Slack channel so {YOUR_NAME} knows it's done
- Post-meeting attendee drafts -- after extracting actions from each meeting, save a copy-paste Slack message to
team/{initials}/post-meeting-drafts/{slug}-{date}.mdwith all actions, owners, deadlines, and key decisions - Information cascade -- when a decision or insight from one meeting affects someone in a different meeting, flag it for {YOUR_NAME} to raise
- Meeting effectiveness tracking -- track which recurring meetings consistently produce actions and decisions vs which produce nothing. After 4 consecutive occurrences with zero actions or decisions, flag it
- Stakeholder contact frequency -- monitor when {YOUR_NAME} last had meaningful contact with key stakeholders. Flag when any key stakeholder hasn't been seen in 2+ weeks
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 · 184 lines · 0 tokens per session scan A b90cdf7ec9e8
cos is an agent published in the GitHub repository motorway-sandbox/product-os (9 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,364 tokens. 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 2026-09-04.
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