update-knowledge-base

# COG Update Knowledge Base Skill

## When to Invoke
- After a release — update product knowledge with new features and changes
- User says "update knowledge base", "update KB", "sync knowledge", "update product docs"
- Periodic maintenance — ensure knowledge base reflects current product state
- After major feature launches, architecture changes, or deprecations

## Agent Mode Awareness

**Check `agent_mode` in `00-inbox/MY-PROFILE.md` frontmatter:**
- If `agent_mode: team` — use parallel agents to scan multiple sources and update multiple knowledge files simultaneously
- If `agent_mode: solo` — process updates sequentially, one knowledge file at a time

## Command: `/update-knowledge-base`

## Pre-Flight Check

1. **Read `00-inbox/MY-INTEGRATIONS.md`** for active data sources and publishing targets
2. **Read `00-inbox/MY-PROFILE.md`** for active projects
3. **Get current timestamp:** Run `date '+%Y-%m-%d %H:%M'` using Bash
4. **Scan existing knowledge base:** Glob `05-knowledge/**/*.md` to understand current state

---

## Execution Strategy

### Phase 1: Determine Update Scope

Ask the user (or infer from context):

```
What triggered this knowledge base update?

a) New release shipped (I'll pull changes from release notes and tracker)
b) Feature launched or updated (I'll document the feature)
c) Architecture or technical change (I'll update technical knowledge)
d) Periodic review (I'll scan for anything that's changed since last update)
e) Custom — describe what needs updating
```

### Phase 2: Gather Update Data

#### Team Mode (parallel agents)

Launch data-gathering agents using the Task tool with `run_in_background: true`:

**Agent: "release-scanner"** (for release-triggered updates)
```
Scan recent releases and release notes for knowledge base updates.

1. Check vault for recent release notes:
   Glob: 04-projects/*/release-notes/*.md
   Read the most recent release notes for each active project

2. If GitHub is active:
   gh release list --repo [CUSTOMIZE: your-org/your-repo] --limit 5 --json tagName,name,body,publishedAt
   Get the latest release details

3. If Linear is active:
   Use ToolSearch to load Linear tools
   Check recently completed cycles and milestones for shipped features

Extract from each source:
- New features added (name, description, user impact)
- Features modified (what changed)
- Features deprecated or removed
- Technical changes (architecture, API, infrastructure)
- Bug fixes that affect documented behavior

Return: structured list of knowledge updates needed
```

**Agent: "existing-kb-auditor"**
```
Audit the current knowledge base for staleness and gaps.

1. Read all files in 05-knowledge/:
   Glob: 05-knowledge/**/*.md

2. For each file, extract:
   - Last updated date (from frontmatter or file modification)
   - Topics covered
   - Products/features documented
   - Any [TODO] or [OUTDATED] markers

3. Cross-reference with active projects from MY-PROFILE.md:
   - Are all active projects represented in the KB?
   - Are there KB entries for discontinued/inactive projects?

4. Check for:
   - Files not updated in >90 days (potentially stale)
   - Topics mentioned in recent release notes but missing from KB
   - Contradictions between KB entries and recent changes

Return: staleness report, gap analysis, and recommended updates
```

**Agent: "tracker-feature-collector"** (for feature-triggered updates)
```
Collect current feature/product state from project trackers.

If Linear is active:
1. Use ToolSearch to load Linear tools
2. List all projects and their current status: mcp__claude_ai_Linear_2__list_projects
3. List all initiatives: mcp__claude_ai_Linear_2__list_initiatives
4. For key initiatives, get details: mcp__claude_ai_Linear_2__get_initiative

If GitHub is active:
1. Check repo README and docs for current feature descriptions
2. Review recent PRs that touch documentation:
   gh pr list --repo [CUSTOMIZE: your-org/your-repo] --state merged --search "label:docs merged:>=[30_DAYS_AGO]" --json number,title,body --limit 20

Return: current product/feature state for knowledge base comparison
```

#### Solo Mode
Run the most relevant agent sequentially based on the update trigger.

### Phase 3: Identify Knowledge Updates

Compare gathered data against existing knowledge base to determine:

1. **New entries needed** — features, products, or topics not yet documented
2. **Updates needed** — existing entries that need modification
3. **Deprecation/removal** — entries for features that no longer exist
4. **Gap filling** — missing context, examples, or cross-references

Present the update plan to the user:

```
Knowledge Base Update Plan:

NEW entries to create:
1. [Topic] — [reason: new feature in v[X]]
2. [Topic] — [reason: gap identified]

UPDATES to existing entries:
1. 05-knowledge/[file].md — [what needs changing]
2. 05-knowledge/[file].md — [what needs changing]

DEPRECATION candidates:
1. 05-knowledge/[file].md — [reason: feature removed in v[X]]

STALE entries (>90 days, may need review):
1. 05-knowledge/[file].md — last updated [date]

Proceed with these updates? (yes / modify plan / skip specific items)
```

**Wait for user approval before making changes.**

### Phase 4: Execute Updates

#### 4.1 Create New Knowledge Entries

For each new entry, use this template:

```markdown
---
type: knowledge
domain: [product/technical/process/architecture]
project: [project-name]
topic: [topic name]
created: [YYYY-MM-DD HH:MM]
last_updated: [YYYY-MM-DD]
source: [release-notes/feature-launch/manual/periodic-review]
version: "1.0"
tags: ["#knowledge", "#[project]", "#[topic-area]"]
related:
  - [path to related KB entry]
  - [path to related project file]
---

# [Topic Title]

## Overview
[Clear, concise description of the topic — what it is, why it matters]

## Current State
[How this feature/system/process works as of the last update]

### Key Details
- **[Detail 1]:** [Value/description]
- **[Detail 2]:** [Value/description]
- **[Detail 3]:** [Value/descri