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 ashermahonin/agentic-skills --skill hypothesis-validatorgit clone --depth 1 https://github.com/ashermahonin/agentic-skillsWrote 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/ashermahonin/agentic-skills/hypothesis-validator)<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/hypothesis-validator"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/hypothesis-validator.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 | $0.00098 | $0.00699 |
| Opus 5 | $0.00049 | $0.00349 |
| Sonnet 5 | $0.00020 | $0.00140 |
| Haiku 4.5 | $0.00010 | $0.00070 |
Grade A, and why
hypothesis-validator 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.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hypothesis Validator
Purpose
Stop the agent from treating opinions as decisions. Force every load-bearing claim through a falsifiable-hypothesis form, then run the cheapest useful test to settle it before commitment.
Inputs
- Read
references/hypothesis-format.md. - List every load-bearing claim attached to the current decision: stack choice, framework choice, model choice, scope inclusion, performance promise, market segment, user behavior assumption.
- For each claim, ask: "what would prove this wrong?" If no answer, refactor the claim until one exists.
- Use Context7 MCP for any claim that depends on current external technology, market, or platform behavior.
Decision process
- For each candidate claim, write a hypothesis card: name, claim, why we believe it, kill criterion, cheapest useful test, owner skill, status.
- Rank hypotheses by impact × uncertainty. The riskiest survives — test it first.
- Choose the cheapest useful test per hypothesis: spike, paper review, eval set, prototype, telemetry probe, A/B, expert interview, vendor docs lookup, regulatory check.
- Run or hand off the test to the matching skill (
service-implementationfor spikes,research-domainfor market,qa-evalfor evals,security-owasp-*for safety claims,cve-zero-day-scannerfor dependency claims). - Record the outcome: supported, disproved, deferred (with reason), or still-open (with planned next test).
- Update the hypothesis register and notify
ai-pdlcof phase-boundary impact.
Decision boundaries
- Use Context7 MCP whenever an external fact gates the test design.
- Keep a decision trace: claim, candidate tests, chosen test, outcome, residual uncertainty.
- Refuse to mark a hypothesis Supported without evidence the test method was sound, not only that the result was favorable.
- Escalate when a "kill criterion" cannot be defined; that is itself the finding.
Decision record
- Hypothesis register entries (one card per claim)
- Ranked test list with cheapest-useful-test rationale
- Test outcomes per hypothesis
- Hypothesis-derived risks pushed into
07-risk-register - Phase-boundary signal to
ai-pdlc
What ships with it
2 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.
- 7d ago First seen · 57 lines · 98 tokens per session scan A a4a4b0596695
hypothesis-validator is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 13d ago), licensed MIT. It adds 98 tokens to every session and 699 once invoked, about $0.0005 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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