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Readiness Framework

Self-assessment framework for the AI Product OS. Measures system maturity across 5 pillars.

Loaded only by /eval and /learning commands. Not loaded during other pipeline stages.

Inspired by Harness Engineering's 8-pillar readiness model, simplified for solo PM use.


5 Pillars

1. Pipeline Compliance

Are all 12 stages being used? Are quality gates enforced?

Level Criteria
1 - Bare Some stages skipped regularly
2 - Guided All stages run, gates checked manually
3 - Enforced Gates block progress mechanically (hooks)
4 - Measured Gate pass/fail rates tracked per cycle
5 - Autonomous Gates auto-adjust based on project risk level

2. Knowledge Currency

Are knowledge files updated after each cycle? Is the learning loop functional?

Level Criteria
1 - Bare Knowledge files unchanged since initial setup
2 - Guided Lessons added after most cycles
3 - Enforced /postmortem + /learning run every cycle, agent files updated
4 - Measured Lesson count tracked, agent improvements verified via /eval
5 - Autonomous Auto-markers regenerate CLAUDE.md from lessons on every commit

3. Enforcement Coverage

What percentage of known anti-patterns have automated checks vs. prose-only?

Level Criteria
1 - Bare All enforcement is prose in CLAUDE.md
2 - Guided Pre-commit hooks catch secrets and file sizes
3 - Enforced Anti-pattern grep checker + function size hooks active
4 - Measured Each postmortem pattern maps to a specific check script
5 - Autonomous New patterns auto-extracted from postmortems into check scripts

4. Token Efficiency

Are commands loading only relevant knowledge? Is context managed?

Level Criteria
1 - Bare All 9 knowledge files loaded for every command
2 - Guided Required Knowledge sections exist per command
3 - Enforced /compact guidance followed; model routing reminders active
4 - Measured Token usage tracked per command type
5 - Autonomous Subagent model tiers applied (Haiku/Sonnet/Opus)

5. Cycle Velocity

How many pipeline stages complete per session? Where does the pipeline stall?

Level Criteria
1 - Bare Pipeline rarely completes a full cycle
2 - Guided Full cycles complete but with manual intervention
3 - Enforced Cycles complete with minimal blocked states
4 - Measured Stage durations tracked, bottlenecks identified
5 - Autonomous Atomic task decomposition + parallel execution operational

Maturity Levels

Level Name Definition
1 Bare Pipeline exists as prose; no automation
2 Guided Knowledge subsetting, model routing docs, manual gates
3 Enforced Hooks active, gates mechanical, anti-pattern checks running
4 Measured Readiness scoring active, postmortem trends tracked, eval assertions passing
5 Autonomous Auto-markers synced, self-improving prompts, subagent tiers operational

How to Score

During /eval or /learning, assess each pillar 1-5 and calculate:

Overall Score = Average of 5 pillar scores

Range Rating
4.5 - 5.0 Autonomous
3.5 - 4.4 Measured
2.5 - 3.4 Enforced
1.5 - 2.4 Guided
1.0 - 1.4 Bare

Added: 2026-03-29 — Readiness framework (Harness Engineering alignment)