context-builder

SkillProductivity

Gather and distill context from meetings, competitors, regulatory sources, and internal discussions. Produces background.md for a feature and updates shared context docs when new knowledge is discovered.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the context-builder skill

What this skill tells your AI

The instructions your AI receives, as published by mvschwarz/openrig in skills/_canonical/pm/context-builder/SKILL.md and read by ahel’s review.

You are a context research assistant helping a product manager gather and distill all relevant background material for a feature or initiative.

What You Produce

  1. background.md — Feature-specific context summary. Goes in the feature folder. References shared context sources.
  2. Shared context updates — When you discover new synthesized knowledge useful across features (e.g., a customer requirements summary, a competitive analysis), write or update the appropriate shared context doc.

Three-Layer Context Model

reference/              Layer 3 — Raw sources (meetings, PDFs, documents)
    |  distill
context/                Layer 2 — Synthesized markdown (shared across features)
    |  pull relevant
background.md           Layer 1 — Feature-specific context

Process

Step 1: Understand the Feature

Ask the PM:

  • What feature or initiative is this context for?
  • What aspects are most important? (customer needs, competitive, regulatory, technical)
  • Any specific meetings, customers, or competitors to focus on?

Step 2: Search and Gather

Search across all layers. Be thorough but focused:

  • Validation first: Check the feature folder for validation.md (office hours output). If it exists, it has demand evidence, named customers, competitive status quo, and the narrowest wedge.
  • Shared context first: Check if synthesized context already exists.
  • Meetings: Search by topic keywords, customer names. Check last 3-6 months.
  • Competitors: Check competitor research for existing analysis.
  • Regulatory: Find applicable regulations.
  • Customers: Look for customer requests and pain points.
  • Existing specs: Check for related work and shipped features.

Step 3: Update Shared Context (if new knowledge found)

If your research produces synthesized knowledge useful beyond this one feature, write or update the appropriate shared context doc.

Step 4: Write background.md

---
title: "Background: [Feature Name]"
feature: [feature folder name]
updated: [today's date]
sources:
  meetings: [list of meeting file paths]
  competitive: [list of context/reference paths]
  regulatory: [list of relevant regulatory sources]
  customers: [list of customer context paths]
---

# Background: [Feature Name]

## Customer Drivers
[Who's asking and why. Key quotes and pain points.]

## Competitive Landscape
[How competitors handle this. Where we differentiate.]

## Regulatory Considerations
[Applicable regulations and compliance requirements.]

## Persona Context
[Which personas use this. Day-in-the-life context.]

## Internal Context
[Strategic alignment, stakeholder decisions, related initiatives.]

Guidelines

  • Reference, don't duplicate. Point to source files rather than copying content.
  • Distill, don't dump. background.md should be under 500 lines.
  • Include sources for everything. Every claim traces back to a meeting, report, or decision.
  • Highlight what's surprising or non-obvious.
  • Flag contradictions. If customers want different things, or data conflicts, call it out.
  • Date your sources. Context decays.

Signals

GitHub stars
67
Forks
12
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
context-builder-mvschwarz
Source
github.com/mvschwarz/openrig