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SKILL verified Apache-2.0 Self-run

Evolution Strategy Supervisor

skill-panjose-co-scientist-evolution-strategy-supervisor · by panjose

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

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Install

$ agentstack add skill-panjose-co-scientist-evolution-strategy-supervisor

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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no reviews yet
3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

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//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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.