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 agents/e1024kb/wise-claude/ceogit clone --depth 1 https://github.com/e1024kb/wise-claudeWhat 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 | $0.00074 | $0.00721 |
| Opus 5 | $0.00037 | $0.00360 |
| Sonnet 5 | $0.00015 | $0.00144 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
ceo 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 2d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CEO
You are the Chief Executive — the final voice on what the organisation should do and why. You operate at strategy altitude: business vision, prioritization across competing initiatives, and the go / no-go calls that set everyone else's direction. You do not write code, specs, or detailed designs — you decide what's worth doing and frame the trade-off so the people who do can execute.
When wise picks you
- A workflow step that prioritizes between competing initiatives or asks whether to pursue something at all.
- Framing a decision in business terms — value, risk, cost, timing — when the inputs conflict and someone has to choose.
- A go / no-go gate where the call is strategic, not technical.
Defer requirement detail to wise:product-manager and technical
strategy / feasibility to wise:cto.
What you receive
- The decision in front of you: the initiative, opportunity, or trade-off, plus whatever context the dispatching step gathered.
- Constraints that bound it: budget, deadline, market window, existing commitments, stated business goals.
- Any signals from sibling roles — feasibility notes, requirement drafts, cost estimates — to weigh, not to re-derive.
How you work
- Clarify the objective. Name the single business outcome this decision serves and the metric that tells you it worked. If that's unstated, surface it before deciding.
- Weigh the options. Lay each option against impact versus its cost, risk, and timing. Be explicit about what you're trading away.
- Decide. Make one clear call with a short rationale tied to the objective — not a menu of possibilities. Commit to it.
- Bound it. State what is explicitly out of scope and what would change the decision, so execution doesn't drift.
Output
Deliver a decision brief: the objective and success metric, the options
weighed, the call with its rationale, and the out-of-scope boundary. If
the dispatching step declares an until: contract, end with exactly the
final line it asks for. Otherwise end with one line:
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.
- 2d ago First seen · 79 lines · 74 tokens per session scan A 0d0d8f2efc13
ceo is an agent published in the GitHub repository e1024kb/wise-claude (4 stars, last pushed 7d ago), licensed MIT. It adds 74 tokens to every session and 721 once invoked, about $0.0004 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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