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 Ahmad-Jaradat-Space/co-scientist-plugin --skill evolving-hypothesesgit clone --depth 1 https://github.com/Ahmad-Jaradat-Space/co-scientist-pluginWrote 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/ahmad-jaradat-space/co-scientist-plugin/evolving-hypotheses)<a href="https://agentmods.dev/skills/ahmad-jaradat-space/co-scientist-plugin/evolving-hypotheses"><img src="https://agentmods.dev/badge/skills/ahmad-jaradat-space/co-scientist-plugin/evolving-hypotheses/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ahmad-jaradat-space/co-scientist-plugin/evolving-hypotheses"><img src="https://agentmods.dev/badge/skills/ahmad-jaradat-space/co-scientist-plugin/evolving-hypotheses.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00099 | $0.01059 |
| Opus 5.5 | $0.00040 | $0.00424 |
| Sonnet 5.5 | $0.00020 | $0.00212 |
| Haiku 4.5 | $0.00010 | $0.00106 |
Grade A, and why
evolving-hypotheses 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evolving hypotheses
You are acting as the Evolution agent. Evolution never edits a hypothesis in place. It produces a new hypothesis that records its parents, so both stay in the tournament and the ranking decides which survives.
A new hypothesis that is not recorded does not exist. Call
co-scientist:hypothesis_record with parent_ids set.
Pick the operator
Choose by what is wrong, not by what sounds interesting. Each operator has a reference file with its procedure and its failure mode; read the one you pick.
| Operator | Use when | Reference |
|---|---|---|
combine |
Two hypotheses each explain part of the phenomenon | reference/combine.md |
simplify |
The mechanism has a broken or unnecessary step | reference/simplify.md |
feasibility |
The mechanism is plausible but untestable as stated | reference/feasibility.md |
out_of_box |
The whole framing is stuck and the field's assumptions need dropping | reference/out-of-box.md |
If a review found a fatal flaw in one claim but the rest holds, simplify is
almost always the right operator: cut the broken claim and see whether what is
left still explains the phenomenon.
Workflow
- [ ] 1. Read the parents and their reviews
- [ ] 2. Name what is wrong, in one sentence
- [ ] 3. Pick the operator and read its reference file
- [ ] 4. Write the new hypothesis
- [ ] 5. Check it is actually different
- [ ] 6. Record it with its parents
- [ ] 7. Review it
1. Read the parents
co-scientist:hypothesis_get for each parent. Read the reviews. Evolution
without the reviews just reshuffles words.
2. Name the defect
Write one sentence: what specifically fails. "The receptor direction is reversed." "The experiment does not discriminate." "It needs a cell type the tissue does not contain."
If you cannot write that sentence, do not evolve the hypothesis. Review it first.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 105 lines · 99 tokens per session scan A ab77a2e9976d
evolving-hypotheses is a skill published in the GitHub repository Ahmad-Jaradat-Space/co-scientist-plugin (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 99 tokens to every session and 1,059 once invoked, about $0.0004 per session on Opus 5.5. 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.
evolving-hypotheses compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| evolving-hypothesesAhmad-Jaradat-Space/co-scientist-plugin | Skill | 1 | 2mo ago | Apache-2.0 | A | 99 | Claude Code, Codex |
| glycoengineeringK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 183 | Claude Code |
| molecular-dynamicsK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 180 | Claude Code |
| molfeatK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 165 | Claude Code |
| rowanK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 100 | Claude Code |
| depmapK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 128 | Claude Code |
| pytdcK-Dense-AI/drug-discovery-agent-skills | Skill | 54 | 5d ago | MIT | A | 150 | Claude Code |