Knowledge Management System

> Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

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Best use case

Knowledge Management System is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. > Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

> Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "Knowledge Management System" skill to help with this workflow task. Context: > Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/afrexai-knowledge-management/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-knowledge-management/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/afrexai-knowledge-management/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Knowledge Management System Compares

Feature / AgentKnowledge Management SystemStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

> Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Knowledge Management System

> Turn tribal knowledge into searchable, maintained organizational intelligence. Stop losing expertise when people leave.

## Phase 1: Knowledge Audit

### Current State Assessment

Score each dimension 1-5 (1=nonexistent, 5=excellent):

| Dimension | Score | Evidence |
|-----------|-------|----------|
| Documentation coverage | | % of processes documented |
| Findability | | Can new hire find answers in <5 min? |
| Freshness | | % of docs updated in last 6 months |
| Contribution culture | | % of team actively contributing |
| Onboarding effectiveness | | Time to productivity for new hires |
| Knowledge retention | | Impact when someone leaves |
| Cross-team sharing | | Teams accessing other teams' knowledge |

**Total Score: ___/35**

Interpretation:
- 28-35: Mature — optimize and maintain
- 21-27: Developing — fill gaps systematically
- 14-20: Basic — needs foundational work
- 7-13: Critical — knowledge is at risk

### Knowledge Risk Register

```yaml
knowledge_risk:
  single_points_of_failure:
    - person: "[Name]"
      unique_knowledge: "[What only they know]"
      risk_if_leaves: "high|medium|low"
      extraction_priority: 1
      extraction_method: "interview|shadowing|recording|pair-work"
  
  undocumented_processes:
    - process: "[Name]"
      frequency: "daily|weekly|monthly|quarterly"
      complexity: "high|medium|low"
      current_owner: "[Name]"
      documentation_priority: 1
  
  tribal_knowledge:
    - topic: "[What people 'just know']"
      holders: ["[Name1]", "[Name2]"]
      impact_area: "[What breaks without it]"
      capture_method: "interview|workshop|write-up"
```

### Knowledge Extraction Interview Guide

For each single-point-of-failure person:

1. **Context**: "I'm documenting [X] so the team isn't dependent on any one person. This protects you too — less interruptions."
2. **Process walk**: "Walk me through [X] from start to finish. I'll record/note."
3. **Decision points**: "Where do you make judgment calls? What factors do you consider?"
4. **Edge cases**: "What are the weird situations that come up? How do you handle them?"
5. **Tools & access**: "What tools, credentials, or access do you need?"
6. **History**: "Why is it done this way? What was tried before?"
7. **Gotchas**: "What are the things that trip people up?"

**Output format**: Write up as a runbook (see Phase 3 templates).

---

## Phase 2: Knowledge Architecture

### Taxonomy Design

```yaml
knowledge_taxonomy:
  # Level 1: Knowledge Types
  types:
    how_to:
      description: "Step-by-step procedures and guides"
      examples: ["Deploy to production", "Process a refund", "Set up dev environment"]
      template: "runbook"
      
    reference:
      description: "Facts, specs, configurations to look up"
      examples: ["API endpoints", "Config values", "Vendor contacts", "Pricing tables"]
      template: "reference_doc"
      
    explanation:
      description: "Why things work the way they do"
      examples: ["Architecture decisions", "Policy rationale", "Historical context"]
      template: "explainer"
      
    decision:
      description: "How to make specific judgment calls"
      examples: ["Escalation criteria", "Approval thresholds", "Priority frameworks"]
      template: "decision_tree"
      
    troubleshooting:
      description: "Diagnosis and fix for known problems"
      examples: ["Error codes", "Common failures", "Debug procedures"]
      template: "troubleshooting_guide"

  # Level 2: Domains (customize per org)
  domains:
    - engineering
    - product
    - sales
    - operations
    - finance
    - hr_people
    - customer_success
    - security
    - legal_compliance

  # Level 3: Topics (within each domain)
  # Example for engineering:
  engineering_topics:
    - architecture
    - deployment
    - monitoring
    - incident_response
    - development_workflow
    - testing
    - security
    - infrastructure
```

### Information Architecture Rules

1. **Maximum 3 levels deep** — if deeper, reorganize
2. **One canonical location per topic** — link, don't duplicate
3. **Every page has an owner** — no orphan docs
4. **Every page has a freshness date** — reviewed within 6 months or flagged
5. **Cross-references over duplication** — "See [X]" beats copy-paste
6. **Search-first design** — assume people search, not browse

### Naming Conventions

```
[DOMAIN]-[TYPE]-[TOPIC]-[SPECIFICS]

Examples:
eng-howto-deploy-production
eng-ref-api-endpoints-v3
sales-decision-pricing-enterprise
ops-troubleshoot-billing-failed-charges
product-explain-auth-architecture
```

### Navigation Structure

```yaml
knowledge_base:
  homepage:
    - quick_links:  # Top 10 most-accessed pages
    - recently_updated:  # Last 10 changes
    - needs_review:  # Stale docs flagged
    
  by_audience:
    new_hire: "[Onboarding path → essential reading list]"
    engineer: "[Dev setup → architecture → deployment → debugging]"
    manager: "[Policies → processes → templates → reports]"
    customer_facing: "[Product knowledge → troubleshooting → escalation]"
    
  by_domain: "[Taxonomy Level 2 domains]"
  by_type: "[How-to | Reference | Explanations | Decisions | Troubleshooting]"
```

---

## Phase 3: Document Templates

### Runbook Template (How-To)

```markdown
# [Title]: [Action verb] + [Object]

**Owner:** [Name]  
**Last verified:** [YYYY-MM-DD]  
**Estimated time:** [X minutes]  
**Difficulty:** Easy | Medium | Advanced  

## Prerequisites
- [ ] [Access/tool/permission needed]
- [ ] [Knowledge assumed]

## Steps

### 1. [First action]
[Specific instruction with exact commands, clicks, or actions]

> ⚠️ [Warning about common mistake at this step]

### 2. [Second action]
[Instructions]

**Expected result:** [What you should see/get]

### 3. [Continue...]

## Verification
- [ ] [How to confirm it worked]
- [ ] [What to check]

## Troubleshooting
| Problem | Likely Cause | Fix |
|---------|-------------|-----|
| [Symptom] | [Why] | [Steps] |

## Related
- [Link to related runbook]
- [Link to reference doc]
```

### Reference Document Template

```markdown
# [Subject] Reference

**Owner:** [Name]  
**Last verified:** [YYYY-MM-DD]  
**Scope:** [What this covers and doesn't cover]

## Overview
[1-2 sentence summary of what this reference contains]

## [Main content organized as tables, lists, or structured data]

| Item | Value | Notes |
|------|-------|-------|
| | | |

## Quick Lookup
[Most frequently needed items at the top]

## Change Log
| Date | Change | By |
|------|--------|-----|
| | | |
```

### Architecture Decision Record (ADR)

```markdown
# ADR-[NNN]: [Title]

**Status:** Proposed | Accepted | Deprecated | Superseded by ADR-[NNN]  
**Date:** [YYYY-MM-DD]  
**Deciders:** [Names]  

## Context
[What situation or problem prompted this decision?]

## Decision
[What was decided and why?]

## Alternatives Considered
| Option | Pros | Cons | Why rejected |
|--------|------|------|-------------|
| [A] | | | |
| [B] | | | |

## Consequences
- **Positive:** [Benefits]
- **Negative:** [Tradeoffs accepted]
- **Risks:** [What could go wrong]

## Review Date
[When should this be revisited?]
```

### Troubleshooting Guide Template

```markdown
# Troubleshooting: [System/Process Name]

**Owner:** [Name]  
**Last verified:** [YYYY-MM-DD]

## Quick Diagnostic

```
[Flowchart as text]
Is [X] happening? 
  → YES: Go to Problem A
  → NO: Is [Y] happening?
    → YES: Go to Problem B
    → NO: Go to Problem C
```

## Problem A: [Symptom Description]

**Likely causes (in order of probability):**
1. [Most common cause]
2. [Second most common]
3. [Rare but possible]

**Fix for Cause 1:**
[Step-by-step resolution]

**Fix for Cause 2:**
[Step-by-step resolution]

**Escalation:** If none of the above work → [who to contact, what info to provide]

## Problem B: [Next symptom]
[Same structure]
```

### Decision Tree Template

```markdown
# Decision Guide: [Topic]

**Owner:** [Name]  
**Last verified:** [YYYY-MM-DD]

## When to use this guide
[Situation that triggers this decision]

## Decision Flow

### Step 1: [First question]
- **If [condition A]** → [Action/next step]
- **If [condition B]** → [Action/next step]
- **If unsure** → [Default action or escalation]

### Step 2: [Second question based on Step 1 answer]
[Continue branching]

## Override conditions
[When to ignore this guide and escalate instead]

## Examples
| Scenario | Decision | Reasoning |
|----------|----------|-----------|
| [Real example] | [What was decided] | [Why] |
```

---

## Phase 4: Contribution System

### Writing Standards

**The 4C Test** (every document must pass all four):
1. **Clear** — Would a new hire understand this? No jargon without definitions.
2. **Correct** — Has this been verified by doing/testing? Not from memory.
3. **Current** — Does this reflect how things work TODAY? Not 6 months ago.
4. **Concise** — Can anything be cut without losing meaning? Cut it.

**Formatting rules:**
- Headers: action-oriented ("Deploy to Production" not "Production Deployment")
- Steps: numbered, one action per step, imperative mood
- Warnings: callout boxes, before the step (not after)
- Code/commands: exact, copy-pasteable, tested
- Screenshots: only if truly needed (they go stale fast)
- Links: to canonical sources, never paste full URLs inline

### Contribution Workflow

```yaml
contribution_workflow:
  create:
    trigger: "New knowledge identified (incident learnings, process change, new tool)"
    steps:
      - choose_template: "Match content type to template"
      - draft: "Write using template structure"
      - self_review: "Run 4C Test checklist"
      - peer_review: "SME validates accuracy"
      - publish: "Add to knowledge base in correct location"
      - announce: "Notify relevant teams/channels"
    
  update:
    trigger: "Existing doc is wrong, incomplete, or stale"
    steps:
      - flag: "Mark as needs-update with reason"
      - update: "Make changes, update 'Last verified' date"
      - review: "If significant change, get peer review"
      - publish: "Update in place"
      - notify: "If behavioral change, announce"
    
  retire:
    trigger: "Doc no longer relevant (deprecated system, changed process)"
    steps:
      - mark: "Status: Deprecated, add redirect to replacement"
      - archive: "Move to archive after 30 days"
      - redirect: "Ensure all links point to replacement"
```

### Incentivizing Contributions

**Making it easy (remove friction):**
- Templates pre-filled with structure
- "Quick capture" channel — dump raw notes, someone structures later
- Post-incident: "What would have helped?" → becomes a doc
- Post-onboarding: new hire documents what was confusing
- Meeting notes → action items include "document [X]"

**Making it visible (social proof):**
- Monthly "top contributors" shoutout
- "Docs champion" rotating role — each sprint, one person owns doc health
- Include documentation in performance criteria
- Knowledge sharing in team meetings (5-min "TIL" segment)

**Making it expected (cultural norms):**
- "If you answered a question twice, write it down"
- PR template includes "Documentation updated? Y/N"
- Incident postmortem includes "Docs to create/update"
- Onboarding feedback includes "What couldn't you find?"

---

## Phase 5: Search & Discovery

### Search Optimization

**Every document should be findable by:**
1. **Title** — descriptive, includes key terms
2. **Tags** — domain, type, audience, technology
3. **Synonyms** — include alternate terms people might search
4. **Problem description** — "When [X] happens" phrasing

**Tag schema:**
```yaml
document_tags:
  domain: "[engineering|product|sales|ops|finance|hr|cs|security|legal]"
  type: "[howto|reference|explanation|decision|troubleshooting]"
  audience: "[all|engineering|management|customer-facing|new-hire]"
  technology: "[list relevant tools/systems]"
  status: "[current|needs-review|deprecated]"
  difficulty: "[beginner|intermediate|advanced]"
```

### Discovery Mechanisms

1. **Contextual links** — Related docs linked at bottom of every page
2. **FAQ collections** — Per-domain "frequently asked" with links to full docs
3. **Onboarding paths** — Curated reading lists by role
4. **Slack/chat bot** — "Ask the KB" — searches and returns relevant docs
5. **Weekly digest** — "New & updated docs this week" email/message
6. **Error-page links** — Application errors link to troubleshooting docs

### Quality Signals

Prioritize search results by:
- **Freshness** — Recently updated > stale
- **Verification** — Peer-reviewed > unreviewed
- **Usage** — Frequently accessed > rarely accessed
- **Completeness** — Fully structured > quick notes

---

## Phase 6: Knowledge Capture Workflows

### Post-Incident Knowledge Capture

After every incident:
1. **Immediate** (within 24h): Raw timeline and resolution steps
2. **Postmortem** (within 5 days): Root cause, contributing factors, action items
3. **Knowledge extraction** (within 10 days):
   - New troubleshooting guide? → Create from postmortem
   - New runbook needed? → Create from resolution steps
   - Existing doc wrong? → Update with correct information
   - Architecture decision needed? → Write ADR
   - Monitoring gap? → Document what to monitor

### Post-Meeting Knowledge Capture

Meeting types that MUST produce knowledge artifacts:
- **Architecture review** → ADR
- **Process change** → Updated runbook
- **Strategy decision** → Decision record
- **Customer feedback pattern** → Product knowledge update
- **Retrospective** → Process improvement doc

### New Employee Knowledge Capture

**First 30 days — new hire documents:**
- What was confusing during onboarding
- Questions that weren't answered by existing docs
- Things that were wrong in existing docs
- Suggestions for improvement

**Template for new hire feedback:**
```yaml
onboarding_feedback:
  week: "[1|2|3|4]"
  couldnt_find: 
    - topic: "[What they looked for]"
      where_looked: "[Where they searched]"
      how_resolved: "[Asked someone? Found eventually? Still unclear?]"
  wrong_or_outdated:
    - doc: "[Which document]"
      issue: "[What's wrong]"
  suggestions:
    - "[Free text improvements]"
```

### Exit Knowledge Transfer

When someone is leaving:
1. **Identify unique knowledge** — What do they know that no one else does?
2. **Schedule extraction sessions** — 1-2 hours per major topic area
3. **Record if possible** — Video walkthroughs of complex processes
4. **Pair them** — Have successor shadow for final 2 weeks
5. **Review their authored docs** — Are they complete? Assign new owners
6. **Document tribal knowledge** — "Why" questions only they can answer

---

## Phase 7: Maintenance & Freshness

### Freshness Policy

```yaml
freshness_policy:
  review_frequency:
    critical_operations: "quarterly"  # Deployment, incident response, security
    standard_processes: "semi-annually"  # Regular workflows
    reference_docs: "annually"  # Specs, contacts, architecture
    explanations: "annually"  # Background, history, rationale
    
  review_process:
    - owner_notified: "2 weeks before due date"
    - review_actions:
        - verify: "Is this still accurate? Test/confirm."
        - update: "Fix any outdated information"
        - stamp: "Update 'Last verified' date"
        - skip: "If can't review, reassign or flag"
    - escalation: "Unreviewed after 30 days → manager notified"
    - stale_threshold: "2x review period without update → flagged as stale"
```

### Content Health Dashboard

```yaml
kb_health:
  date: "[YYYY-MM-DD]"
  
  coverage:
    total_documents: 0
    by_type:
      howto: 0
      reference: 0
      explanation: 0
      decision: 0
      troubleshooting: 0
    by_domain: {}
    gaps_identified: []
    
  freshness:
    current: 0  # Reviewed within policy
    needs_review: 0  # Due for review
    stale: 0  # Past review deadline
    deprecated: 0
    freshness_rate: "0%"  # current / (current + needs_review + stale)
    
  quality:
    peer_reviewed: "0%"
    using_templates: "0%"
    has_owner: "0%"
    has_tags: "0%"
    
  usage:
    searches_per_week: 0
    failed_searches: 0  # Searches with no results
    top_10_pages: []
    pages_never_accessed: 0
    
  contribution:
    docs_created_this_month: 0
    docs_updated_this_month: 0
    unique_contributors: 0
    contribution_rate: "0%"  # contributors / total team size
```

### Quarterly Knowledge Review

**Agenda (60 min):**
1. Dashboard review (10 min) — health metrics trend
2. Gap analysis (15 min) — what's missing? What questions keep being asked?
3. Stale doc triage (15 min) — update, deprecate, or reassign owners
4. Failed searches review (10 min) — what are people searching for and not finding?
5. Process improvements (10 min) — what's working, what isn't?

---

## Phase 8: Knowledge-Driven Automation

### Automated Knowledge Triggers

```yaml
automation_triggers:
  incident_resolved:
    action: "Create task: 'Write troubleshooting guide for [incident title]'"
    assignee: "Incident commander"
    due: "+10 days"
    
  new_hire_started:
    action: "Generate personalized onboarding reading list from KB by role"
    
  doc_stale:
    action: "Notify owner, CC manager if unreviewed after 14 days"
    
  repeated_question:
    threshold: "Same question asked 3+ times in support/Slack"
    action: "Create task: 'Document answer to [question]'"
    
  process_changed:
    trigger: "PR merged that changes workflow/process"
    action: "Check if related docs need updating, create task if yes"
    
  failed_search:
    threshold: "Same search term fails 5+ times/week"
    action: "Flag as gap, create task to write missing doc"
```

### Knowledge-Powered Chatbot Design

```yaml
kb_chatbot:
  flow:
    1_receive_question: "User asks in designated channel"
    2_search: "Semantic search across KB"
    3_respond:
      found_match: "Return relevant doc link + summary"
      partial_match: "Return closest docs + 'Did you mean...?'"
      no_match: "Log as gap, route to human expert, create doc task"
    4_feedback: "Was this helpful? 👍/👎"
    5_improve: "Use feedback to tune search, identify doc improvements"
    
  sources:
    - knowledge_base_docs
    - slack_saved_answers  # Curated from Slack threads
    - incident_postmortems
    - meeting_notes_tagged_as_knowledge
```

---

## Phase 9: Cross-Team Knowledge Sharing

### Knowledge Sharing Mechanisms

| Mechanism | Frequency | Format | Audience |
|-----------|-----------|--------|----------|
| "TIL" channel | Daily | Short post (1-3 sentences + link) | All |
| Brown bag lunch | Bi-weekly | 20-min presentation + Q&A | Cross-team |
| Architecture review | Monthly | 45-min deep dive + ADR | Engineering |
| Customer insight share | Monthly | Top 5 patterns + implications | Product + CS + Sales |
| Postmortem review | Per incident | Written + optional walkthrough | Engineering + ops |
| New tool/technique demo | As needed | 15-min demo + doc link | Relevant teams |
| Quarterly knowledge review | Quarterly | Dashboard + gap analysis | Leadership |

### Cross-Team Knowledge Map

```yaml
knowledge_map:
  engineering:
    produces: ["Architecture docs", "Runbooks", "API specs", "ADRs"]
    consumes_from:
      product: ["PRDs", "User research", "Roadmap"]
      customer_success: ["Bug patterns", "Feature requests", "Usage data"]
      sales: ["Technical requirements", "Integration needs"]
      
  product:
    produces: ["PRDs", "User research", "Roadmap", "Release notes"]
    consumes_from:
      engineering: ["Technical feasibility", "Architecture constraints"]
      customer_success: ["Feature requests", "Churn reasons"]
      sales: ["Deal requirements", "Competitive intel"]
      
  customer_success:
    produces: ["FAQ", "Troubleshooting guides", "Best practices"]
    consumes_from:
      engineering: ["Release notes", "Known issues"]
      product: ["Feature docs", "Roadmap"]
      
  sales:
    produces: ["Battlecards", "Competitive intel", "Use case docs"]
    consumes_from:
      product: ["Feature docs", "Roadmap", "Pricing"]
      customer_success: ["Case studies", "Success metrics"]
      engineering: ["Technical capabilities", "Integration docs"]
```

---

## Phase 10: Metrics & ROI

### Knowledge Management KPIs

| Metric | Target | Measurement |
|--------|--------|-------------|
| Time to answer | <5 min for documented topics | Sample timing tests |
| New hire time to productivity | Reduce by 30% | First solo task date |
| Repeated questions | Decrease 50% in 6 months | Support ticket analysis |
| Doc coverage | >80% of critical processes | Audit against process list |
| Freshness rate | >85% within review policy | Dashboard metric |
| Contribution rate | >40% of team contributing monthly | Contributor count |
| Search success rate | >80% find what they need | Search analytics |
| Failed search rate | <10% of searches | Search analytics |
| Knowledge reuse | >60% of team using KB weekly | Usage analytics |

### ROI Calculation

```
Knowledge Management ROI:

Time Saved:
  Reduced question-answering = [hours/week] × [avg hourly cost] × 52
  Faster onboarding = [weeks saved] × [new hires/year] × [weekly cost]
  Faster incident resolution = [hours saved/incident] × [incidents/year] × [hourly cost]
  
Risk Reduced:
  Key person dependency = [probability of departure] × [knowledge reconstruction cost]
  Compliance documentation = [audit prep hours saved] × [hourly cost]
  
Quality Improved:
  Fewer repeated mistakes = [error rate reduction] × [cost per error]
  Consistent processes = [variance reduction] × [rework cost]
  
Total Annual Value = Time Saved + Risk Reduced + Quality Improved
Investment = Tool cost + Time spent maintaining KB + Training
ROI = (Total Annual Value - Investment) / Investment × 100
```

---

## Phase 11: Scoring & Quality

### Document Quality Rubric (0-100)

| Dimension | Weight | 0-2 (Poor) | 3-5 (Adequate) | 6-8 (Good) | 9-10 (Excellent) |
|-----------|--------|------------|-----------------|-------------|-------------------|
| Accuracy | 20% | Unverified, possibly wrong | Mostly correct | Verified, accurate | Tested, peer-reviewed |
| Completeness | 15% | Major gaps | Covers basics | Comprehensive | Edge cases included |
| Clarity | 15% | Confusing, jargon-heavy | Understandable | Clear, well-structured | A new hire gets it |
| Findability | 10% | No tags, bad title | Some tags | Good tags, clear title | Synonyms, cross-refs |
| Freshness | 15% | >12 months stale | Within annual review | Within semi-annual | Within quarterly |
| Template compliance | 10% | No structure | Partial template | Full template | Template + extras |
| Actionability | 10% | Theory only | Some steps | Clear steps | Copy-paste ready |
| Ownership | 5% | No owner | Owner assigned | Owner active | Owner + backup |

**Score interpretation:**
- 90-100: Exemplary — reference model for other docs
- 75-89: Good — meets standards
- 60-74: Acceptable — needs minor improvements
- 40-59: Below standard — needs significant work
- 0-39: Critical — rewrite from scratch

### Knowledge Base Health Score (0-100)

| Dimension | Weight | Metric |
|-----------|--------|--------|
| Coverage | 20% | % of critical processes documented |
| Freshness | 20% | % of docs within review policy |
| Quality | 15% | Average document quality score |
| Usage | 15% | % of team using KB weekly |
| Contribution | 15% | % of team contributing monthly |
| Search effectiveness | 15% | % of searches finding results |

---

## Edge Cases

### Small Team (<10 people)
- Start with a single shared doc/wiki, not a full KB platform
- Focus on: runbooks for critical processes, onboarding guide, decision log
- One person owns KB health (part-time, not full-time)
- Review quarterly, not monthly

### Remote/Distributed Teams
- Default to written over verbal knowledge sharing
- Record important meetings/decisions (not all meetings)
- Async-first: every decision documented, not just discussed
- Time zone coverage: ensure docs cover "what to do when the expert is asleep"

### Rapid Growth (Doubling in 6 months)
- Prioritize onboarding docs above all else
- Implement "new hire documents what they learn" from day 1
- Assign knowledge buddies — each new person paired with a doc mentor
- Weekly new-hire cohort Q&A → captured and documented

### Regulated Industry
- Map compliance requirements to documentation requirements
- Version control with audit trail (who changed what, when)
- Approval workflows for regulated content
- Retention policies aligned with regulations

### Post-Merger/Acquisition
- Map both organizations' knowledge structures
- Identify overlaps and gaps
- Prioritize: "how do we work NOW" docs over historical
- Freeze archives of legacy systems/processes

### Migrating from Scattered Docs
- Don't try to migrate everything — start fresh with new structure
- Import only: still-accurate, frequently-used docs
- Redirect old locations to new ones
- Set a sunset date for old system
- "If it's not in the new KB, it doesn't exist" (after migration period)

---

## Natural Language Commands

| Command | Action |
|---------|--------|
| "Audit our knowledge management" | Run Phase 1 assessment, generate risk register |
| "Design our KB structure" | Create taxonomy and navigation architecture |
| "Write a runbook for [X]" | Generate using runbook template |
| "Write an ADR for [X]" | Generate architecture decision record |
| "Create a troubleshooting guide for [X]" | Generate using troubleshooting template |
| "Review KB health" | Generate health dashboard and identify gaps |
| "Plan knowledge extraction for [person]" | Generate interview guide and schedule |
| "Set up freshness tracking" | Create review schedule and notification rules |
| "Design onboarding knowledge path for [role]" | Curate reading list from KB |
| "Analyze failed searches" | Review search gaps and create tasks |
| "Generate quarterly KB report" | Full metrics dashboard with recommendations |
| "Plan KB migration from [source]" | Create migration plan with prioritization |

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