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/kw-compound

Extract and save learnings from a completed knowledge work session. Saves to docs/knowledge/ so future plans automatically find them.

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From plugin
compound-knowledge-plugin
4316 skills5 agents
Install
$ npx -y skills add everyinc/compound-knowledge-plugin --skill kw-compound --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/kw-compound

Context preview

The summary Claude sees to decide when to auto-load this skill.

Extract and save learnings from a completed knowledge work session. Saves to docs/knowledge/ so future plans automatically find them.

SKILL.md

kw-compound.SKILL.md
name: kw:compound
description: Extract and save learnings from a completed knowledge work session. Saves to docs/knowledge/ so future plans automatically find them.

Compound

Close the loop. Extract what you learned and save it where future work will find it.

When to Use

  • After completing a plan, campaign, analysis, or strategy session
  • "Compound this session", "Save what we learned", "What should we remember?"
  • After a data correction, process fix, or strategic insight
  • At the end of any meaningful work session

Process

Step 1: Identify learnings

Scan the current session for compoundable insights. Look for:

| Type | Signals | | --------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | | **Insight** | "We discovered...", surprising finding, counter-intuitive result | | **Playbook** | Repeatable process that worked, step-by-step that others could follow | | **Correction** | Wrong assumption fixed, data source clarified, definition updated | | **Pattern** | Something that keeps recurring, systemic observation |

**Extract 1-3 learnings max.** Quality over quantity. If nothing is worth saving, say so:

> "Nothing from this session seems worth saving as a standalone learning. The work is captured in the plan/deliverables."

For each learning, draft:

**Learning:** [One sentence — what we now know]
**Type:** [insight | playbook | correction | pattern]
**Why it matters:** [One sentence — how this changes future work]

Step 2: Get user approval

Present the drafted learnings and ask:

> "Found [N] learnings worth saving. Review and approve?"

Show each learning with its classification. User can:

  • Approve as-is
  • Edit the wording
  • Skip individual learnings
  • Add learnings you missed

**Do not save anything without approval.**

Step 3: Check for duplicates

For each approved learning, search existing knowledge:

Grep: [key phrases] in docs/knowledge/
Grep: [key phrases] in docs/solutions/

If a similar learning already exists:

  • Show the existing entry
  • Ask: "Update existing or save as new?"
  • If updating, edit the existing file

Step 3.5: Check for stale knowledge

After identifying what to save, launch the stale knowledge checker:

Launch Task agent: `compound-knowledge:research:stale-knowledge-checker`

  • Pass: the new learning(s) being saved
  • Returns: existing entries that may be contradicted or superseded

If stale entries are found, present them to the user:

> "This new learning may conflict with existing knowledge: > - **[existing file]** says [X], but the new learning says [Y] > - Recommendation: [Update / Remove / Keep both] > > Want me to update the old entry?"

<critical_requirement> Agents return TEXT only. They must NOT write or delete files. Only the orchestrating compound skill writes files — both new learnings and updates to stale entries. </critical_requirement>

Step 4: Save locally

Write each learning to `docs/knowledge/`:

**Filename:** `docs/knowledge/{descriptive-slug}.md`

Create the directory if it doesn't exist: `mkdir -p docs/knowledge/`

**File format:**

---
type: [insight | playbook | correction | pattern]
tags: [relevant keywords for future search]
confidence: [high | medium | low]
created: [today's date]
source: [brief description of what triggered this]
---

# [Learning Title]

[2-4 sentences explaining the learning. Be specific enough that someone reading this in 3 months understands what happened and why it matters.]

## Context

[What you were doing when you discovered this.]

## Implication

[How this should change future work. Be concrete: "When doing X, always check Y first."]

Step 5: Confirm and offer next steps

## Compounded

**Saved:**
- docs/knowledge/{filename}.md

**This learning will be surfaced by /kw:plan** when future work touches:
- [list the tags that would trigger retrieval]

Use AskUserQuestion:

**Question:** "Learnings saved. What next?"

**Options:** 1. **Run `/kw:plan`** — Start a new planning cycle (the learnings will be found) 2. **Push to Proof** — Share the learnings for team review 3. **Done** — Session complete

Important Rules

  • **1-3 learnings max per session.** If you're saving 5 things, you're not filtering enough.
  • **Approval required.** Never auto-save. The user decides what's worth remembering.
  • **Be specific.** "Use the right data source" is useless. "Revenue metrics come from [specific dashboard], not [other source] which overcounts by ~$X" is useful.
  • **Duplicates are waste.** Always check before creating. Update existing entries when possible.
  • **Confidence matters.** Mark `low` if based on one data point. Mark `high` if verified across multiple sessions or with data.
  • **Tags are for retrieval.** Choose tags that `/kw:plan`'s grep search would match on. Think: "What future question would this answer?"

Pipeline Mode

When invoked with `disable-model-invocation` context (e.g., from an orchestrator or automation):

  • Skip all AskUserQuestion prompts
  • Use sensible defaults for all choices
  • Write output files without waiting for confirmation
  • Proceed to the next suggested skill automatically
  • Output structured results that the calling context can parse
Read more
Ships withcompound-knowledge-plugin

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

Get the whole plugin

Other skills on compound-knowledge-plugin.