kwcompound

# 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- Pass: the new learning(s) being saved - Returns: existing entries that may be contradicted or superseded If stale entries are found, present them to the user: 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:** ```markdown --- 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