agentsclimarketplace
Sign in

Talk stoneham product brain

Skill jscraik/Agent-Skills/Plugins/aidevcon/skills/talk-stoneham-product-brain

Explains the Product Brain talk and helps design curated product-memory systems for AI-assisted product work: knowledge structure, provenance, synthesis cadence, ownership, and agent-ready context packets. Use when the user asks about product context for AI, product knowledge management, product documentation for LLMs, or building a maintained product brain.From its SKILL.md

Install
npx -y skills add jscraik/Agent-Skills --skill talk-stoneham-product-brain

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 8 stars8 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.8 KB, 502 tokens by cl100k_base, as published. Nobody here has run it

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

  1. Use outline.md for the talk thesis, concept map, and safe application boundaries.
  2. Use quote.md when the answer needs a short supporting excerpt.
  3. Use transcript.md only to confirm what remained after safety redaction.
  4. 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:

  1. Identify the relevant concept from outline.md.
  2. Answer in 2-5 sentences.
  3. Add one short excerpt from quote.md only if it strengthens the answer.
  4. State when the bundle does not cover a requested detail.

When applying the talk to the user's work:

  1. Choose a small set of curated knowledge categories.
  2. Record provenance and owner for each category.
  3. Define when synthesis happens and who reviews it.
  4. Create agent-ready packets with goals, constraints, and decisions.
  5. 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: <one sentence>
  • Key concepts: <3-5 bullets>
  • Practical takeaway: <one action the team can take safely>

Design Artifact

  • Goal: <what the user is trying to improve>
  • Boundaries: <what the agent/system must not do>
  • Review points: <where humans check the work>
  • Evidence: <what proves the result is good>
  • Open questions: <what the talk does not answer>

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.

Examples

User: How do I build a product brain? Response shape: Provide categories, ownership, synthesis cadence, and review gates.

User: Can you ingest our product tickets? Response shape: Decline intake work and offer a curated export template.

What ships with it: 4 files

2.9 KB alongside SKILL.md

agents/

Keep looking

Skills are one crate of 326,750. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.