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 shinpr/nautilus --skill hypothesis-disciplinegit clone --depth 1 https://github.com/shinpr/nautilusWrote 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/shinpr/nautilus/hypothesis-discipline)<a href="https://agentmods.dev/skills/shinpr/nautilus/hypothesis-discipline"><img src="https://agentmods.dev/badge/skills/shinpr/nautilus/hypothesis-discipline/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/shinpr/nautilus/hypothesis-discipline"><img src="https://agentmods.dev/badge/skills/shinpr/nautilus/hypothesis-discipline.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 | $0.00045 | $0.00756 |
| Opus 5.5 | $0.00018 | $0.00302 |
| Sonnet 5.5 | $0.00009 | $0.00151 |
| Haiku 4.5 | $0.00005 | $0.00076 |
Grade A, and why
hypothesis-discipline 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hypothesis Discipline
Core Principle
A hypothesis is not a guess. A hypothesis selected for validation needs a clear decision, evidence criteria, and a stopping condition.
Hypothesis Characteristics
- Hypotheses exist at every level of the OST hierarchy (see product-principles skill)
- Each hypothesis has a target level attribute indicating which OST level it addresses
- Hypotheses follow an ADR-style lifecycle — a single file tracks the full journey from draft to conclusion
- Preserve rejected and invalidated hypotheses as learning assets
Hypothesis Lifecycle
draft → testing → validated → adopted
→ rejected (validated but not adopted)
→ invalidated (disproven by evidence)
→ inconclusive (evidence gathered but insufficient to confirm or deny)
→ timeout (deadline passed, decision needed: continue or stop)
Hypothesis File Schema
The authoritative schema is defined in references/hypothesis-template.md. Key fields:
id: HYPO-NNNlevel: outcome / opportunity / solution / assumptionstatus: draft / testing / validated / invalidated / inconclusive / adopted / rejected / timeoutconfidence: scores for the risk dimensions that can change the hypothesis decision, on the product-principles 0-10 scaletime-budgetanddeadline: include when time or calendar limits affect the validation decision
Validation Criteria Requirements
A hypothesis entering validation defines:
- We believe that — the hypothesis statement
- We'll know we're right when — measurable success criteria
- We'll know we're wrong when — measurable failure criteria
- Validation method — how we will test (prototype, data analysis, interview, code spike, market research)
- Stopping condition — the evidence, time limit, or cost limit that ends this validation
Time Budget and Cutoff
- Give a validation a time budget when exploration or evidence collection can expand
- Add a deadline when a calendar cutoff changes the decision
- When deadline passes without conclusion → status becomes
timeout - Timeout forces a decision: extend (with justification), pivot, or abandon
- End validation at its evidence, time, or cost boundary
What ships with it
1 file 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 · 76 lines · 45 tokens per session scan A 5093b5382c64
hypothesis-discipline is a skill published in the GitHub repository shinpr/nautilus (7 stars, last pushed 10d ago), licensed MIT. It adds 45 tokens to every session and 756 once invoked, about $0.0002 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.
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