Install
$ agentstack add skill-panjose-co-scientist-evolution-strategy-supervisor ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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//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.
- 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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: panjose
- Source: panjose/Co-Scientist
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.