flywheel
Knowledge flywheel health monitoring. Checks velocity, pool depths, staleness. Triggers: "flywheel status", "knowledge health", "is knowledge compounding".
Best use case
flywheel is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Knowledge flywheel health monitoring. Checks velocity, pool depths, staleness. Triggers: "flywheel status", "knowledge health", "is knowledge compounding".
Teams using flywheel should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/flywheel/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How flywheel Compares
| Feature / Agent | flywheel | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Knowledge flywheel health monitoring. Checks velocity, pool depths, staleness. Triggers: "flywheel status", "knowledge health", "is knowledge compounding".
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.
SKILL.md Source
# Flywheel Skill
Monitor the knowledge flywheel health.
## The Flywheel Model
```
Sessions → Transcripts → Forge → Pool → Promote → Knowledge
↑ │
└───────────────────────────────────────────────┘
Future sessions find it
```
**Velocity** = Rate of knowledge flowing through
**Friction** = Bottlenecks slowing the flywheel
## Execution Steps
Given `$flywheel`:
### Step 1: Measure Knowledge Pools
```bash
# Count top-level artifact files (avoid counting directories)
LEARNINGS=$(find .agents/learnings -maxdepth 1 -type f 2>/dev/null | wc -l)
PATTERNS=$(find .agents/patterns -maxdepth 1 -type f 2>/dev/null | wc -l)
RESEARCH=$(find .agents/research -maxdepth 1 -type f 2>/dev/null | wc -l)
RETROS=$(find .agents/retros -maxdepth 1 -type f 2>/dev/null | wc -l)
echo "Learnings: $LEARNINGS"
echo "Patterns: $PATTERNS"
echo "Research: $RESEARCH"
echo "Retros: $RETROS"
```
### Step 2: Check Recent Activity
```bash
# Recent learnings (last 7 days)
find .agents/learnings -maxdepth 1 -type f -mtime -7 2>/dev/null | wc -l
# Recent research
find .agents/research -maxdepth 1 -type f -mtime -7 2>/dev/null | wc -l
```
### Step 3: Detect Staleness
```bash
# Old artifacts (> 30 days without modification)
find .agents/ -name "*.md" -mtime +30 2>/dev/null | wc -l
```
### Step 3.5: Check Cache Health
```bash
if command -v ao &>/dev/null; then
# Get citation report (cache metrics)
CITE_REPORT=$(ao metrics cite-report --json --days 30 2>/dev/null)
if [ -n "$CITE_REPORT" ]; then
HIT_RATE=$(echo "$CITE_REPORT" | jq -r '.hit_rate // "unknown"')
UNCITED=$(echo "$CITE_REPORT" | jq -r '(.uncited_learnings // []) | length')
STALE_90D=$(echo "$CITE_REPORT" | jq -r '.staleness["90d"] // 0')
echo "Cache hit rate: $HIT_RATE"
echo "Uncited learnings: $UNCITED"
echo "Stale (90d uncited): $STALE_90D"
fi
else
# ao-free fallback: compute approximate metrics from files
echo "Cache health (ao-free fallback):"
# Learnings modified in last 30 days (active pool)
ACTIVE_30D=$(find .agents/learnings/ -name "*.md" -mtime -30 2>/dev/null | wc -l | tr -d ' ')
echo "Active learnings (30d): $ACTIVE_30D"
# Forge candidates awaiting promotion
FORGE_PENDING=$(ls .agents/forge/*.md 2>/dev/null | wc -l | tr -d ' ')
echo "Forge candidates pending: $FORGE_PENDING"
# Citation tracking (if citations.jsonl exists)
if [ -f .agents/ao/citations.jsonl ]; then
CITATION_COUNT=$(wc -l < .agents/ao/citations.jsonl | tr -d ' ')
UNIQUE_CITED=$(grep -o '"artifact_path":"[^"]*"' .agents/ao/citations.jsonl 2>/dev/null | sort -u | wc -l | tr -d ' ')
echo "Total citations: $CITATION_COUNT"
echo "Unique learnings cited: $UNIQUE_CITED"
else
echo "No citation data (citations.jsonl not found)"
fi
# Session outcomes (if outcomes.jsonl exists)
if [ -f .agents/ao/outcomes.jsonl ]; then
OUTCOME_COUNT=$(wc -l < .agents/ao/outcomes.jsonl | tr -d ' ')
echo "Session outcomes recorded: $OUTCOME_COUNT"
fi
fi
```
### Step 4: Check ao CLI Status
```bash
if command -v ao &>/dev/null; then
ao metrics flywheel status 2>/dev/null || echo "ao metrics flywheel status unavailable"
ao status 2>/dev/null || echo "ao status unavailable"
ao maturity --scan 2>/dev/null || echo "ao maturity unavailable"
ao anti-patterns 2>/dev/null || echo "ao anti-patterns unavailable"
ao badge 2>/dev/null || echo "ao badge unavailable"
# Knowledge maintenance
ao dedup --merge 2>/dev/null || true
ao contradict 2>/dev/null || true
ao constraint review 2>/dev/null || true
ao curate status 2>/dev/null || true
ao metrics health 2>/dev/null || true
ao metrics cite-report --days 30 2>/dev/null || true
# Active pruning: archive stale, evict low-utility, and curate noisy uncited learnings
ao maturity --expire --archive 2>/dev/null || true
ao maturity --evict --archive 2>/dev/null || true
ao maturity --curate --archive 2>/dev/null || true
# Retrieval quality: use the representative live corpus when it exists
if [ -d cli/cmd/ao/testdata/retrieval-bench-live ]; then
ao retrieval-bench --live --corpus cli/cmd/ao/testdata/retrieval-bench-live --json 2>/dev/null || true
fi
else
echo "ao CLI not available — using file-based metrics"
# Pool inventory
echo "Pool depths:"
for pool in learnings patterns forge knowledge research retros; do
COUNT=$(ls .agents/${pool}/*.md 2>/dev/null | wc -l | tr -d ' ')
echo " $pool: $COUNT"
done
# Global patterns
GLOBAL_COUNT=$(ls ~/.codex/patterns/*.md 2>/dev/null | wc -l | tr -d ' ')
echo " global patterns: $GLOBAL_COUNT"
# Check for promotion-ready learnings (see references/promotion-tiers.md)
echo "See: references/promotion-tiers.md for tier definitions"
fi
```
### Step 4.5: Process Metrics (from skill telemetry)
If `.agents/ao/skill-telemetry.jsonl` exists, use `jq` to extract: invocations by skill, average cycle time per skill, gate failure rates. Include in health report (Step 6) under `## Process Metrics`.
### Step 5: Validate Artifact Consistency
Cross-reference validation: scan knowledge artifacts for broken internal references.
Use `scripts/artifact-consistency.sh` (method documented in `references/artifact-consistency.md`).
Default allowlist lives at `references/artifact-consistency-allowlist.txt`; use `--no-allowlist` for a full raw audit.
Health indicator: >90% = Healthy, 70-90% = Warning, <70% = Critical.
### Step 6: Write Health Report
**Write to:** `.agents/flywheel-status.md`
```markdown
# Knowledge Flywheel Health
**Date:** YYYY-MM-DD
## Pool Depths
| Pool | Count | Recent (7d) |
|------|-------|-------------|
| Learnings | <count> | <count> |
| Patterns | <count> | <count> |
| Research | <count> | <count> |
| Retros | <count> | <count> |
## Velocity (Last 7 Days)
- Sessions with extractions: <count>
- New learnings: <count>
- New patterns: <count>
## Artifact Consistency
- References scanned: <count>
- Broken references: <count>
- Consistency score: <percentage>%
- Status: <Healthy/Warning/Critical>
## Cache Health
- Hit rate: <percentage>%
- Uncited learnings: <count>
- Stale (90d uncited): <count>
- Status: <Healthy/Warning/Critical>
## Retrieval Quality
- Live corpus coverage: <percentage or unavailable>
- Live corpus learnings: <count or unavailable>
- Status: <Healthy/Warning/Critical>
## Health Status
<Healthy/Warning/Critical>
## Friction Points
- <issue 1>
- <issue 2>
## Recommendations
1. <recommendation>
2. <recommendation>
```
### Step 7: Report to User
Tell the user:
1. Overall flywheel health
2. Knowledge pool depths
3. Recent activity
4. Any friction points
5. Recommendations
## Health Indicators
| Metric | Healthy | Warning | Critical |
|--------|---------|---------|----------|
| Learnings/week | 3+ | 1-2 | 0 |
| Stale artifacts | <20% | 20-50% | >50% |
| Research/plan ratio | >0.5 | 0.2-0.5 | <0.2 |
| Cache hit rate | >80% | 50-80% | <50% |
## Cache Eviction
Read `references/cache-eviction.md` for the full eviction pipeline (passive tracking → confidence decay → maturity scan → archive).
## Key Rules
- **Monitor regularly** - flywheel needs attention
- **Address friction** - bottlenecks slow compounding
- **Feed the flywheel** - run $retro and $post-mortem
- **Prune stale knowledge** - archive old artifacts
## Examples
**User says:** `$flywheel` — Counts pool depths, checks recent activity, validates artifact consistency, writes health report to `.agents/flywheel-status.md`.
**Hook trigger:** After `$post-mortem` — Compares current vs historical metrics, flags velocity drops and friction points.
## Troubleshooting
| Problem | Cause | Solution |
|---------|-------|----------|
| All pool counts zero | `.agents/` directory missing or empty | Run `$post-mortem` or `$retro` to seed knowledge pools |
| Velocity always zero | No recent extractions (last 7 days) | Run `$retro` or `$post-mortem` to extract and index learnings |
| "ao CLI not available" | ao command not installed or not in PATH | Install ao CLI or use manual pool counting fallback |
| Stale artifacts >50% | Long time since last session or inactive repo | Run `$provenance --stale` to audit and archive old artifacts |
## Reference Documents
- [references/artifact-consistency.md](references/artifact-consistency.md)
- [references/promotion-tiers.md](references/promotion-tiers.md)
## Local Resources
### references/
- [references/artifact-consistency-allowlist.txt](references/artifact-consistency-allowlist.txt)
- [references/artifact-consistency.md](references/artifact-consistency.md)
- [references/cache-eviction.md](references/cache-eviction.md)
- [references/promotion-tiers.md](references/promotion-tiers.md)
### scripts/
- `scripts/artifact-consistency.sh`
- `scripts/validate.sh`Related Skills
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