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Compound Knowledge

Workflows for knowledge work that compounds over time. The knowledge work equivalent of Compound Engineering.

Read the story: How to Build a Command Center That Keeps You Sane

The Loop

/kw:brainstorm   -->  Brain dump, pull references, find the shape
/kw:plan         -->  Structure into an actionable plan
/kw:confidence   -->  Gut-check what you know vs. don't (callable at any point)
/kw:review       -->  Strategic alignment + data accuracy check
/kw:work         -->  Execute the plan, produce deliverables
/kw:compound     -->  Save learnings for next time

Each cycle makes the next one faster. /kw:plan searches docs/knowledge/ for past learnings saved by /kw:compound. Knowledge compounds.

Install

Inside a Claude Code session:

/plugin marketplace add EveryInc/compound-knowledge-plugin
/plugin install compound-knowledge

Getting Started

Brainstorm something. A problem, a campaign, notes from a meeting:

/kw:brainstorm I need to figure out our Q2 content strategy

When you're ready to commit to a direction:

/kw:plan

After any meaningful session, save what you learned:

/kw:compound

Next time you brainstorm or plan something related, those learnings surface automatically.

Workflows

Brainstorm

Start here. Paste a meeting transcript, brain dump raw thoughts, or describe a problem. Auto-searches your knowledge base and past plans for relevant context, then extracts key decisions, open questions, constraints, and tensions.

Plan

Structure a brainstorm into an actionable plan. Launches parallel research agents to find past work and saved learnings. Outputs a Pyramid Principle plan (lead with the answer) in three detail tiers — Quick for gut checks, Standard for most plans, Deep for multi-quarter strategies.

Confidence

Callable at any point in the loop. Pauses to honestly assess what Claude knows and doesn't know — in plain language, not a table. Produces a "confident about / less confident about / my recommendation" breakdown, then offers specific actions to close gaps.

Review

Two reviewers check your work in parallel:

  • Strategic Alignment — Is the goal clear? Is the hypothesis falsifiable? Are we solving the right problem?
  • Data Accuracy — Are numbers sourced? Are baselines explicit? Is data fresh?

Findings are merged and grouped P1 (blocks shipping) / P2 (should fix) / P3 (nice to have).

Work

Execute a plan. Break it into tasks, group by dependency, run independent tasks in parallel. Writes execution log back to the plan file so /kw:compound has concrete material to learn from.

Compound

Extract 1-3 learnings from a session. Checks for stale knowledge that the new learning contradicts. Saves to docs/knowledge/ with searchable YAML frontmatter.

How It Works

  1. You brainstorm and plan something
  2. /kw:plan searches docs/knowledge/ — finds past insights
  3. You execute and review
  4. /kw:compound saves what you learned to docs/knowledge/
  5. Next time you plan something related, step 2 finds it

No configuration needed. Works with any project that has a plans/ directory.

The knowledge files are plain markdown, git-tracked, and greppable:

# docs/knowledge/trial-conversion-timing.md
---
type: insight
tags: [trials, conversion, campaigns]
confidence: high
created: 2026-02-15
source: Q1 trial campaign analysis
---

# Trial Conversion Timing

Extended trial periods (30 days vs 7 days) increase conversion rate but
delay revenue recognition. Net positive after 60 days.

Components

Type Count Description
Skills 6 brainstorm, plan, confidence, review, work, compound
Review Agents 2 strategic-alignment, data-accuracy
Research Agents 3 past-work-researcher, knowledge-base-researcher, stale-knowledge-checker

Customization

The plugin reads your project's CLAUDE.md for:

  • Business context and goals (used by the strategic alignment reviewer)
  • Data source hierarchy (used by the data accuracy reviewer)
  • Style guides and conventions (used during execution)

If your project doesn't have a CLAUDE.md, the workflows still work — they just won't have project-specific context.

License

MIT