evolution-strategy-supervisor

evolution-strategy-supervisor is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 19 tokens per session (546 once invoked), scanned A, original, Apache-2.0.

A decision step that selects one concrete strategy for improving a research hypothesis during an evolution round. The strategy may focus on evidence, clarity, practicality, simplification, combination, or divergence, depending on the research setup.

In plain words
What is it for?
Use it when a research process is continuing and a parent hypothesis and its review findings are available.
Why use it?
It gives the next research round a single direction instead of allowing unfocused or conflicting changes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when a research process is continuing and a parent hypothesis…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/panjose/co-scientist/evolution-strategy-supervisor
Install

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.

Any agent
npx skills add panjose/Co-Scientist --skill evolution-strategy-supervisor
Clone the repo
git clone --depth 1 https://github.com/panjose/Co-Scientist

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for evolution-strategy-supervisor

README.md
[![agentmods](https://agentmods.dev/badge/skills/panjose/co-scientist/evolution-strategy-supervisor.svg)](https://agentmods.dev/skills/panjose/co-scientist/evolution-strategy-supervisor)
Your own site
<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>
Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 546 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 6d ago against content hash dea3100c3f8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

skills/evolution-strategy-supervisor/SKILL.md · 65 lines

What it actually says

evolution-strategy-supervisor

Goal:

  • Choose exactly one concrete evolution strategy for the active evolution round.

Inputs:

  • research_plan/RESEARCH_PLAN.json
  • state/STRATEGY_PLAN.json
  • selected parent hypotheses/<id>/HYPOTHESIS.json artifacts 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_action is continue_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_evolution
      • coherence_evolution
      • feasibility_evolution
      • simplification_evolution
    • For multi_island, prefer strategies that combine or diverge across parents:
      • inspiration_evolution
      • combination_evolution
      • out_of_box_evolution
    • Use the parent review bundle to choose the most corrective or most leverageable move for this round.
  • 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:

  1. Read the required artifacts.
  2. Confirm the parent set and island-selection mode for the current round.
  3. Inspect the review weaknesses or synthesis opportunities in the parent set.
  4. Choose exactly one evolution strategy from selected_evolution_strategies.
  5. 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.
Changes

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.

  1. 6d ago First seen · 65 lines · 19 tokens per session scan A dea3100c3f8a

Subscribe to this mod's changes

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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