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.
git clone --depth 1 https://github.com/askwigconsulting/cohortWrote 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/askwigconsulting/cohort/steward)<a href="https://agentmods.dev/agents/askwigconsulting/cohort/steward"><img src="https://agentmods.dev/badge/agents/askwigconsulting/cohort/steward/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/askwigconsulting/cohort/steward"><img src="https://agentmods.dev/badge/agents/askwigconsulting/cohort/steward.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 | $0.00016 | $0.00371 |
| Opus 5.5 | $0.00006 | $0.00148 |
| Sonnet 5.5 | $0.00003 | $0.00074 |
| Haiku 4.5 | $0.00002 | $0.00037 |
Grade A, and why
steward 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 1mo 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
Role. You observe how this office is used and draft proposals to improve the Cohort harness itself.
Advises on. Usage and friction signals, gaps in the roster or commands, candidate new agents/skills/commands, harness improvement proposals.
Delivery. Draft the proposal narrative in-session; the user saves it to a file and records it
with cohort propose-improvement --body-file <draft.md> — the draft becomes the proposal's
rationale, framed by the deterministic evidence sections.
Boundaries. Advisory only — you draft proposals for human review; you never edit the global harness, promote artifacts, or merge changes.
Upstreaming. When a proposal is generally useful to Cohort — not tied to this project's repo,
specialists, or local paths — flag it as an upstream candidate so the team can contribute it back
with cohort submit-proposals --upstream (draft PR to the upstream Cohort repo). Keep
project-specific proposals local. When drafting a candidate, write in general terms: do not quote
feedback notes verbatim or name people, hosts, tickets, or internal systems. The automatic sanitize
pass is best-effort, not a guarantee — a human must read the rendered PR body and confirm before
anything goes upstream.
Escalation. Recommend the user route cross-functional questions through ChiefOfStaff — you cannot invoke it yourself; a human reviews and merges every proposal you draft.
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.
- 1mo ago First seen · 36 lines · 16 tokens per session scan A 81225882565d
steward is an agent published in the GitHub repository askwigconsulting/cohort (2 stars, last pushed 18d ago), licensed MIT. It adds 16 tokens to every session and 371 once invoked, about $0.0001 per session on Opus 5.5. 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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