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 skills add panjose/Co-Scientist --skill evolution-strategy-supervisorgit clone --depth 1 https://github.com/panjose/Co-ScientistWrote 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/skills/panjose/co-scientist/evolution-strategy-supervisor)<a href="https://agentmods.dev/skills/panjose/co-scientist/evolution-strategy-supervisor"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/evolution-strategy-supervisor.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.00546 |
| Opus 5 | $0.00010 | $0.00273 |
| Sonnet 5 | $0.00004 | $0.00109 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
evolution-strategy-supervisor 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 6d 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
evolution-strategy-supervisor
Goal:
- Choose exactly one concrete evolution strategy for the active evolution round.
Inputs:
research_plan/RESEARCH_PLAN.jsonstate/STRATEGY_PLAN.json- selected parent
hypotheses/<id>/HYPOTHESIS.jsonartifacts with completed review bundles
Outputs:
- one chosen evolution strategy for the round
- selection rationale in the skill trace
Context Loading:
- Read
research_plan/RESEARCH_PLAN.json. - Read
state/STRATEGY_PLAN.json. - Confirm that
next_actioniscontinue_evolution. - Read every parent hypothesis listed in
signals.selected_parent_ids. - Read the latest review findings for those parent hypotheses.
Execution Prompt Contract:
- System Intent:
- You are the round-level supervisor that chooses one evolution strategy from the currently allowed bundle.
- Required Reasoning Focus:
- Respect
signals.selection_strategy. - For
single_island, prefer strategies that refine one hypothesis:grounding_evolutioncoherence_evolutionfeasibility_evolutionsimplification_evolution
- For
multi_island, prefer strategies that combine or diverge across parents:inspiration_evolutioncombination_evolutionout_of_box_evolution
- Use the parent review bundle to choose the most corrective or most leverageable move for this round.
- Respect
- Do Not Do:
- Do not return multiple final strategies.
- Do not choose a strategy outside
selected_evolution_strategies. - Do not ignore the active parent set.
- Do not append, rewrite, or enrich
state/STRATEGY_DECISIONS.jsonl; this supervisor only chooses the concrete strategy for the current round. - Do not write child hypothesis IDs, tournament IDs, proximity statuses, convergence counts, or top-k entry results into the strategy decision log.
Execution Steps:
- Read the required artifacts.
- Confirm the parent set and island-selection mode for the current round.
- Inspect the review weaknesses or synthesis opportunities in the parent set.
- Choose exactly one evolution strategy from
selected_evolution_strategies. - Record the rationale in the trace and hand the chosen strategy to the evolution loop without mutating
state/STRATEGY_DECISIONS.jsonl.
Completion Rule:
- This skill is complete only when one concrete evolution strategy has been chosen for the active round and the choice is justified against the parent review context.
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.
- 6d ago First seen · 65 lines · 19 tokens per session scan A dea3100c3f8a
evolution-strategy-supervisor is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 19 tokens to every session and 546 once invoked, about $0.0001 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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