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 JunMystery/Agent-Guidance-Python --skill product-capabilitygit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote 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/junmystery/agent-guidance-python/product-capability)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/product-capability"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/product-capability/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/junmystery/agent-guidance-python/product-capability"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/product-capability.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 | $0.00059 | $0.00906 |
| Opus 5.5 | $0.00024 | $0.00362 |
| Sonnet 5.5 | $0.00012 | $0.00181 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
product-capability 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 1mo 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.
This is a copy
100% identical to product-capability — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Capability
This skill turns product intent into explicit engineering constraints.
Use it when the gap is not "what should we build?" but "what exactly must be true before implementation starts?"
When to Use
- A PRD, roadmap item, discussion, or founder note exists, but the implementation constraints are still implicit
- A feature crosses multiple services, repos, or teams and needs a capability contract before coding
- Product intent is clear, but architecture, data, lifecycle, or policy implications are still fuzzy
- Senior engineers keep restating the same hidden assumptions during review
- You need a reusable artifact that can survive across harnesses and sessions
Canonical Artifact
If the repo has a durable product-context file such as PRODUCT.md, docs/product/, or a program-spec directory, update it there.
If no capability manifest exists yet, create one using the template at:
docs/examples/product-capability-template.md
The goal is not to create another planning stack. The goal is to make hidden capability constraints durable and reusable.
Non-Negotiable Rules
- Do not invent product truth. Mark unresolved questions explicitly.
- Separate user-visible promises from implementation details.
- Call out what is fixed policy, what is architecture preference, and what is still open.
- If the request conflicts with existing repo constraints, say so clearly instead of smoothing it over.
- Prefer one reusable capability artifact over scattered ad hoc notes.
Inputs
Read only what is needed:
- Product intent
- issue, discussion, PRD, roadmap note, founder message
- Current architecture
- relevant repo docs, contracts, schemas, routes, existing workflows
- Existing capability context
PRODUCT.md, design docs, RFCs, migration notes, operating-model docs
- Delivery constraints
- auth, billing, compliance, rollout, backwards compatibility, performance, review policy
Core Workflow
1. Restate the capability
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.
- 1mo ago First seen · 142 lines · 59 tokens per session scan A 80adddd72a5e
product-capability is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 906 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to product-capability, differing in 2 lines, and is treated as a copy.
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