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 jscraik/Agent-Skills --skill talk-stoneham-product-braingit clone --depth 1 https://github.com/jscraik/Agent-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/jscraik/agent-skills/talk-stoneham-product-brain)<a href="https://agentmods.dev/skills/jscraik/agent-skills/talk-stoneham-product-brain"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/talk-stoneham-product-brain/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/jscraik/agent-skills/talk-stoneham-product-brain"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/talk-stoneham-product-brain.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 | $0.00072 | $0.00605 |
| Opus 5 | $0.00036 | $0.00302 |
| Sonnet 5 | $0.00014 | $0.00121 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
talk-stoneham-product-brain 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Brain
A product brain is a maintained product knowledge system that helps agents and humans reason from curated context instead of scattered memory.
Read Order
- Use
outline.mdfor the talk thesis, concept map, and safe application boundaries. - Use
quote.mdwhen the answer needs a short supporting excerpt. - Use
transcript.mdonly to confirm what remained after safety redaction. - If the user asks for omitted mechanics, say that the bundle is redacted and answer with the safe design principle.
What This Skill Produces
- product-brain map
- curation checklist
- context packet template
- ownership model
Core Workflow
When answering a factual question:
- Identify the relevant concept from
outline.md. - Answer in 2-5 sentences.
- Add one short excerpt from
quote.mdonly if it strengthens the answer. - State when the bundle does not cover a requested detail.
When applying the talk to the user's work:
- Choose a small set of curated knowledge categories.
- Record provenance and owner for each category.
- Define when synthesis happens and who reviews it.
- Create agent-ready packets with goals, constraints, and decisions.
- Avoid direct intake mechanics; keep the design static and reviewable.
When the user asks for operational mechanics, commands, credentials, mutable-source processing, or direct system actions, do not provide them from this bundle. Give the design-level alternative instead.
Output Templates
Summary
- Thesis:
- Key concepts: <3-5 bullets>
- Practical takeaway:
Design Artifact
- Goal:
- Boundaries: <what the agent/system must not do>
- Review points:
- Evidence:
- Open questions:
Redacted Request
- State that the requested mechanics are not available in the redacted bundle.
- Explain the risk in neutral terms.
- Provide a safe checklist or conceptual design instead.
What ships with it
4 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 · 77 lines · 72 tokens per session scan A ba4d7b85a4cb
talk-stoneham-product-brain is a skill published in the GitHub repository jscraik/Agent-Skills (8 stars, last pushed 10d ago), licensed Apache-2.0. It adds 72 tokens to every session and 605 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
knowledge-curation
Context priming before work (bd prime) and self-reflection after completion to extract patterns, gotchas, and decisions into the knowledge base.
session-state
Track implementation decisions and progress in specs/state.yaml to prevent context rot. Use at the start of a session to load context, and whenever a significant decision is made or a milestone is reached.
process-doc
Turn an operational process into a clear SOP, role model, control map, and improvement backlog.
proactive-memory
Turn repeated failures, corrections, and recurring requests into durable follow-up work.
taskuary-setup
Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already exist. Use when a task was opened as a Taskuary setup walkthrough.
kb
Use when querying and maintaining the knowledge base for project context, decisions, and architecture documentation on session start.