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 hypothesis-evolve-simplificationgit 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/hypothesis-evolve-simplification)<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-evolve-simplification"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-evolve-simplification.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 | $0.00023 | $0.00674 |
| Opus 5 | $0.00012 | $0.00337 |
| Sonnet 5 | $0.00005 | $0.00135 |
| Haiku 4.5 | $0.00002 | $0.00067 |
Grade A, and why
hypothesis-evolve-simplification 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 7d 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
hypothesis-evolve-simplification
Goal:
- Generate exactly one child hypothesis that preserves the core idea while reducing unnecessary complexity.
Inputs:
research_plan/RESEARCH_PLAN.json- selected parent
hypotheses/<id>/HYPOTHESIS.jsonartifacts - parent review artifacts
- active
state/STRATEGY_PLAN.json
Outputs:
hypotheses/<id>/HYPOTHESIS.jsonhypotheses/<id>/HYPOTHESIS.mdhypotheses/<id>/ORIGIN.json
Context Loading:
- Open
skills/shared-references/schema-index.md. - Read
packages/agent_contracts/hypothesis.pyand confirm the exactHypothesisContractshape before writinghypotheses/<id>/HYPOTHESIS.json. - Read
research_plan/RESEARCH_PLAN.json. - Read
state/STRATEGY_PLAN.json. - Read each selected parent hypothesis and its review bundle.
- Confirm that the round selected
simplification_evolution.
Execution Prompt Contract:
- System Intent:
- You are distilling the parent hypothesis into a leaner, cleaner, easier-to-test child without collapsing it into triviality.
- Required Reasoning Focus:
- Remove surplus assumptions and over-specified branches.
- Preserve one clear causal core.
- Keep the experiment path minimal but decisive.
- Do Not Do:
- Do not oversimplify into a generic statement.
- Do not lose the falsifiable prediction.
- Quality Floor:
- The child must directly address at least one specific weakness from the parent review bundle.
origin.content.statementmust name concrete materials, catalysts, reaction conditions, mechanistic variables, or experimental targets from the parent and research goal.origin.content.mechanismmust explain a causal chain; do not write only generic phrases such asimproved mechanism,targeted improvement, orreview-identified weaknesses.origin.content.experimental_designmust include 3-6 numbered steps with measurable readouts, controls, or decision thresholds.- Do not use generic refinement placeholder steps such as
Apply targeted improvement,Characterize with standard techniques,Benchmark against parent, orValidate improvement quantitatively. - If the research plan, parent hypothesis, or parent review bundle is missing, stop and report the missing artifact instead of guessing.
- Output Shape:
- Emit the canonical
HypothesisContract. origin.strategy:simplification_evolution- Keep
experimental_designminimal and decisive.
- Emit the canonical
Execution Steps:
- Open
skills/shared-references/schema-index.md, then readpackages/agent_contracts/hypothesis.pybefore writinghypotheses/<id>/HYPOTHESIS.json. - Identify complexity that can be removed without losing the core insight.
- Produce exactly one simplified child hypothesis.
- Persist canonical
HYPOTHESIS.json,HYPOTHESIS.md, andORIGIN.json. - Validate the emitted hypothesis artifact.
Completion Rule:
- This skill is complete only when one simplified child hypothesis has been written in canonical form.
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.
- 7d ago First seen · 68 lines · 23 tokens per session scan A 4cb1a69ca348
hypothesis-evolve-simplification is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 23 tokens to every session and 674 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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