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 recipe-validategit 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/recipe-validate)<a href="https://agentmods.dev/skills/shinpr/nautilus/recipe-validate"><img src="https://agentmods.dev/badge/skills/shinpr/nautilus/recipe-validate.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 | $0.00038 | $0.01255 |
| Opus 5 | $0.00019 | $0.00628 |
| Sonnet 5 | $0.00008 | $0.00251 |
| Haiku 4.5 | $0.00004 | $0.00126 |
Grade A, and why
recipe-validate 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 2d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context: Validate hypotheses using appropriate methods based on risk type. Invoke hypothesis-verifier for bias-free validation design. Record results in hypothesis files.
Required Skills [LOAD BEFORE EXECUTION]
- [LOAD IF NOT ACTIVE]
hypothesis-discipline— lifecycle, evidence, confidence, and stopping conditions - [LOAD IF NOT ACTIVE]
product-principles— 4 Risks and validation sufficiency
Conditional Skills [LOAD WHEN TRIGGERED]
- WHEN the selected method is prototype validation: [LOAD IF NOT ACTIVE]
prototype-guide - WHEN the selected method uses business-model, market, or viability analysis: [LOAD IF NOT ACTIVE]
business-context
Delegate validation design to hypothesis-verifier for bias-free assessment.
Execution Decision Flow
1. Hypothesis Assessment
Input: Use the path or text supplied with the explicit skill invocation. If no input was supplied and the target cannot be inferred unambiguously, ask for it.
Read the target hypothesis file(s). Understand:
- What is being tested (the hypothesis statement)
- Which risk dimension is primary (Value / Usability / Feasibility / Viability)
- Current confidence scores
- Validation stopping condition, including a time budget or deadline when present
- Parent Opportunity context
2. Validation Design
Invoke hypothesis-verifier to design the validation:
- hypothesis-verifier operates in a separate context to prevent confirmation bias
- It designs the test without knowing the orchestrator's expectations
- It defines success/failure criteria independently
Present the validation design to the user when executing it would commit external resources, change the product outcome, or exceed the confirmed time or cost boundary:
- Proposed validation method
- Success and failure criteria
- Required resources and time estimate
- Risk of the validation approach itself
When any of these conditions applies, end the current turn with the validation design as the workflow output. Execute that validation only after the user confirms it in a later turn.
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.
- 2d ago Changed · +2 lines 96d619aef1be
- 7d ago First seen · 117 lines · 38 tokens per session scan A bcf094c0c69a
recipe-validate is a skill published in the GitHub repository shinpr/nautilus (4 stars, last pushed 6d ago), licensed MIT. It adds 38 tokens to every session and 1,255 once invoked, about $0.0002 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.
Other skills, from other repositories
productspec
Use when implementing, reviewing, planning, or changing work governed by a Product Spec. Treat .product-spec.md files as the product contract for the work.
productspec-authoring
Writes, validates, and converts ProductSpec files (.product-spec.md), the Markdown format for recording product intent before implementation. Use when authoring a new Product Spec, converting an existing PRD or feature doc into one, validating spec files locally or in CI, or recording how a spec's intent changed over…
product-principles
Defines 4 Risks confidence thresholds, OST hierarchy levels, Knowledge Pyramid tiers, and state design requirements. Use when evaluating user stories, setting confidence scores, referencing OST levels, scoping MVP, or determining validation sufficiency.
recipe-define
Orchestrate PRD creation from validated hypotheses — standard PRD output with 4 Risks confidence and hypothesis traceability.
recipe-validate
Orchestrate hypothesis validation through type-appropriate methods — prototypes, code analysis, market research, and expert review.
hypothesis-discipline
Manages hypothesis lifecycle, enforces validation criteria, time budgets, and confidence scoring rules. Use when creating hypotheses, updating confidence scores, setting validation criteria, handling timeouts, or recording validation results.