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 product-principlesgit 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/product-principles)<a href="https://agentmods.dev/skills/shinpr/nautilus/product-principles"><img src="https://agentmods.dev/badge/skills/shinpr/nautilus/product-principles/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/product-principles"><img src="https://agentmods.dev/badge/skills/shinpr/nautilus/product-principles.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 | $0.00049 | $0.01366 |
| Opus 5 | $0.00024 | $0.00683 |
| Sonnet 5 | $0.00010 | $0.00273 |
| Haiku 4.5 | $0.00005 | $0.00137 |
Grade A, and why
product-principles 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 8d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Management Principles
Core Philosophy
- Hypothesis Until Proven: Every assumption is a hypothesis until validated with evidence. Treat unvalidated ideas as hypotheses, not facts
- Value Traceability: Preserve the links needed to connect a decision or implementation back to its supporting outcome and evidence
- Proportionate Validation: Use cost x risk x reversibility to determine sufficient confidence
- Proportionate Artifacts: Keep durable decisions in repo artifacts when a downstream consumer will reuse them; no-change and reuse are valid outcomes
Opportunity Solution Tree (OST) Hierarchy
Use this hierarchy to distinguish outcomes, opportunities, solutions, assumptions, and experiments when those distinctions affect the current decision:
Outcome
├── Product Outcome (team-controllable product goals)
│ NSM connects Product Outcome ↔ Business Outcome
└── Business Outcome (business results Product Outcome contributes to)
Product Outcome
└── Opportunity (user problems, needs, desires)
└── Solution (approaches to address the opportunity = feature candidates)
└── Assumption (premises underlying the solution = hypotheses)
└── Experiment (methods to validate the hypothesis)
Level Definitions
| Level | Granularity | Artifact | Description |
|---|---|---|---|
| Business Outcome | Largest | docs/product/vision.md |
Business results the product contributes to |
| Product Outcome | Large | docs/product/vision.md |
Team-controllable product goals |
| Opportunity | Large | docs/discovery/opportunities/ |
User problems, needs, desires |
| Solution | Medium | PRD (docs/prd/) |
Feature candidates addressing an Opportunity |
| Assumption | Small | docs/discovery/hypotheses/ |
Premises underlying a Solution |
| User Story | Smallest | Within PRD | Minimum unit of value with sufficient evidence for its material risks |
4 Risks (Authoritative Definition)
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.
- 8d ago First seen · 112 lines · 49 tokens per session scan A 8a3d7bdc0303
product-principles is a skill published in the GitHub repository shinpr/nautilus (4 stars, last pushed 7d ago), licensed MIT. It adds 49 tokens to every session and 1,366 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.