# framework-health

Assesses Mycelium framework process health across completed development cycles and quality gates.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 47
- Author: haabe
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/haabe/mycelium/tree/HEAD/plugins/mycelium/skills/framework-health/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/framework-health

## What it does

The skill evaluates Mycelium workflow efficiency by parsing `.claude/canvas/cycle-history.yml`. It calculates cycle duration across scales, tracks discard distribution across phases, and validates ICE confidence calibration for product-leaf work. It also audits theory gate pass rates to spotlight rubber stamps or blocking bottlenecks.

A product workspace must have at least 5 completed cycles on record. When fewer entries exist, the tool halts with an insufficient data notice. If the project self-hosts Mycelium via `plugins/mycelium/plugin.json`, it switches to a dogfood summary from `.claude/memory/corrections.md` instead of cycle velocity metrics.

Running this skill standalone outside Mycelium skips the required canvas records, leaving the analysis without source files.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add haabe/mycelium --skill framework-health -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/framework-health/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/framework-health/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add haabe/mycelium --skill framework-health -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/framework-health/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add haabe/mycelium --skill framework-health -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/framework-health/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install haabe/mycelium framework-health
```

2. **Manually: put the files in place**
- File: `.github/skills/framework-health/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add haabe/mycelium --skill framework-health -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/haabe/mycelium --path plugins/mycelium/skills/framework-health
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/framework-health/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add haabe/mycelium --skill framework-health -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/haabe/mycelium/tree/HEAD/plugins/mycelium/skills/framework-health/SKILL.md

## When to use it
- measure delivery velocity across development cycles
- detect late-stage task discards in Phase 7 and above
- verify ICE confidence calibration against actual outcomes
- spot rubber-stamped or excessively blocking theory gates

## Example prompts
- Run the framework-health evaluation on our recent cycle history
- Analyze Mycelium process health and theory gate effectiveness
- Check our confidence calibration factor and discard trends

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 70fb2a1d9110760c.

BEGIN THIRD-PARTY FILE 70fb2a1d9110760c
```text
---
name: framework-health
description: "Evaluate Mycelium's own process effectiveness. Measures cycle velocity, discard trends, confidence calibration, gate effectiveness, regression rate. Run quarterly or every 20 cycles."
metadata:
  instruction_budget: "50"
  framework_dependency: "mycelium"
  framework_dependency_note: "This skill is designed to run within the Mycelium framework (https://github.com/haabe/mycelium). Standalone use will skip the canvas state, theory gates, and harness behavior the skill assumes. Install: /plugin install mycelium@haabe-mycelium."
---

# Framework Health Check

Mycelium evaluates its own process. This is triple-loop learning — the framework assessing whether it is getting better at producing good outcomes.

## When to Use

- Quarterly review (scheduled)
- After 20 completed leaf cycles (triggered by cycle-history.yml count)
- When process friction is suspected
- Before major framework changes (baseline measurement)

## Workflow

### 1. Load Cycle Data

Read `.claude/canvas/cycle-history.yml`.

**Framework-self-host detection** (per `engine/cycle-learning.md#framework-on-framework-exemption`): if the project root contains `plugins/mycelium/plugin.json` AND `CLAUDE.md` begins with `# Mycelium:`, this is the framework dogfooding itself. Skip the cycle-count gate and route to a corrections-graduation summary:
- Count entries in `.claude/memory/corrections.md` (total, and ×graduated-to-mechanism in the last 90 days).
- Read `.claude/memory/cluster-instances.md` and list clusters at-or-above their graduation criterion that are not yet graduated (this is the framework analogue of "actual outcome vs predicted ICE").
- Skip cycle-derived dimensions (velocity, discard rate, confidence calibration, regression rate) — they do not apply. Still run Steps 2b, 4b, 4c, 4d.

Otherwise (product project, not framework-self-host): if fewer than 5 cycles recorded, report:
"Insufficient cycle data for framework health assessment. [N] cycles recorded; minimum 5 needed. Continue recording outcomes."

### 2. Measure Five Dimensions

For each dimension, compute the metric and compare against trend (if prior assessments exist):

**Cycle Velocity**:
- Average days from diamond creation to completion, grouped by scale
- Trend: improving / stable / degrading
- If degrading: flag for investigation

**Discard Rate**:
- Count of discards per lifecycle phase
- Average discard phase (1-10 scale)
- Trend: shifting earlier (good) / shifting later (bad) / stable
- If >50% of discards at Phase 7+: flag "late discard pattern"

**Confidence Calibration**:
- **Cycle-class scope (per `engine/cycle-learning.md#cycle-class`)**: ONLY `product-leaf` cycles feed calibration. `meta-dogfood` (framework-self-development) and `observation` (strategic-process reflection) cycles carry no ICE *by design* — they are EXCLUDED, not missing. This matches `cycle-history.yml#calibration_summary`, which already excludes them from aggregates; the dimension was previously computed over all cycles, which is the bug this fixes.
```
END THIRD-PARTY FILE 70fb2a1d9110760c

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