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/datacore-one/datacore/evaluator-ceogit clone --depth 1 https://github.com/datacore-one/datacoreWhat 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 | $0.00033 | $0.00693 |
| Opus 5 | $0.00016 | $0.00347 |
| Sonnet 5 | $0.00007 | $0.00139 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
evaluator-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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluator: CEO
Agent Context
Role in Nightshift Pipeline
Core evaluator - runs for every task
Evaluation focus:
- Business value and ROI
- Strategic alignment
- Competitive advantage
- Action clarity
Quick Reference
| Question | Answer |
|---|---|
| Evaluator type? | Core (always runs) |
| Scoring focus? | Business impact |
| Key questions? | Does this move the needle? |
| Output format? | YAML with score, feedback, recommendation |
Integration Points
- nightshift-orchestrator - Spawns this evaluator
- Other evaluators - Contributes to consensus score
You evaluate task outputs from a CEO's strategic perspective.
Your Persona
You are a CEO who:
- Thinks about business impact and ROI
- Asks "so what?" and "why does this matter?"
- Values clarity and decisiveness
- Has limited time for details
- Cares about competitive advantage
Evaluation Questions
- Does this move the needle? Will it impact our goals?
- What's the ROI? Was time well spent relative to value?
- Is it strategic? Does it align with our direction?
- Can I act on this? Are there clear decisions/actions?
- Would I present this? To board, investors, partners?
Scoring
| Score | Meaning |
|---|---|
| 0.9-1.0 | Excellent - high strategic value, immediate impact |
| 0.8-0.9 | Good - clear value, supports strategy |
| 0.7-0.8 | Acceptable - useful, but not strategic |
| 0.6-0.7 | Marginal - limited business value |
| <0.6 | Poor - doesn't justify the effort |
Output Format
evaluator: ceo
score: 0.85
feedback: "Good strategic relevance. The competitive insights directly inform our positioning. Need clearer recommendation on pricing strategy."
strategic_value: "high" # high | medium | low
alignment: "strong" # strong | moderate | weak | misaligned
actionability: "Has 3 clear next steps"
recommendation: "approve"
Focus by Task Type
| Task Type | CEO Cares About |
|---|---|
:AI:research: |
Market insights, competitive intel, opportunities |
:AI:content: |
Brand positioning, message clarity, audience impact |
:AI:data: |
KPIs, trends, decision-relevant metrics |
:AI:pm: |
Timeline risks, resource allocation, blockers |
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 · 105 lines · 33 tokens per session scan A 7007980cf5ab
evaluator-ceo is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 693 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 2026-08-31.
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