score

name	score
description	Track and analyze the Autonomy Score — the experiment's primary KPI. Measures what percentage of Mentilead operational decisions required no human input over a rolling period. Three modes: update decision counts, review the current score with chapter-appropriate context (5-second check), or analyze trends across months. Use when updating the autonomy log, checking the score, or analyzing decision patterns over time.
disable-model-invocation	true

GrowthOS Autonomy Tracker

Step 0: Detect & Route

Before starting any mode, determine the current state and route to the right step.

Read Current State

1. Read marketing/MEMORY.md and marketing/STATUS.md
2. If marketing/ does NOT exist: tell the user to run the init skill first and stop
3. Read references/experiment-thesis.md — required by the Experiment Layer rules in CLAUDE.md
4. Check if marketing/experiment/autonomy-log.md exists. If not, create it from templates/autonomy-log.md
5. Read experiment_chapter from STATUS.md frontmatter (default: "Chapter 1: Foundation")
6. Parse the Monthly Summary table to get the current month's row and previous month's row

Route by Intent

Detect intent from the user's message and route:

• Mentions logging/adding/recording decisions → Step 1
• Mentions score/check/where do we stand → Step 2
• Mentions trend/history/over time/chart → Step 3

Present Options

If the user's intent is not clear from their message, present these options:

Autonomy Tracker — {experiment_chapter}:
Current month: {YYYY-MM}
Score: {score}% ({autonomous} autonomous / {total} decisions)
Trend: {direction} vs last month ({prev_score}%)

1. Update Log — record additional decisions
2. Score Review — current score with context
3. Trend Analysis — 6-month rolling view

Route to the appropriate step based on the user's choice or detected intent.

Step 1: Update Log

Batch-update decision counts for the current month. Works alongside the observation logger — adds to existing counters, never replaces.

Gather Counts

Read current month's row from marketing/experiment/autonomy-log.md Monthly Summary table.

If no row for the current month exists, show current zeroed state.

Ask each question in sequence:

• "Any additional autonomous decisions to log?" (number, or "none")
• "Any additional human escalations?" (number, or "none")
• "Any agent failures?" (number, or "none")

For each non-zero answer, optionally ask: "Which system/agent?" (for system breakdown tracking)

Update Monthly Summary Table

Update marketing/experiment/autonomy-log.md:

1. Find or create the row for the current month (format: YYYY-MM)
2. Add to existing counters — do NOT replace (the observation logger may have already incremented)
3. Recalculate Total: autonomous + human_escalations
4. Recalculate Score: autonomous / total * 100 (rounded to nearest integer, format as {score}%)
5. Agent Failures are tracked but NOT part of the score denominator (per thesis definition: score = autonomous / (autonomous + escalations))

Update System Breakdown

Update or create the System Breakdown section for the current month in marketing/experiment/autonomy-log.md.

The system breakdown section for each month follows this format:

### {YYYY-MM}

| System | Autonomous | Escalated | Failures |
|--------|-----------|-----------|----------|
| {system_name} | {n} | {n} | {n} |

If a section for the current month already exists, update counters for existing systems or add new rows. If no section exists, create one.

Optional Notes

Ask: "Any notes for this month?" (free text, appended to Notes column)

If the user declines, leave the Notes column as-is (preserve existing value or use —).

Confirm to User

Updated {YYYY-MM}:
Autonomous: {n} | Escalations: {n} | Failures: {n}
Score: {score}% ({direction} vs last month)

Session Log & State Update

1. Append to marketing/logs/{YYYY-MM-DD}.md:

   - **Autonomy Tracker** — Updated {YYYY-MM} log: {autonomous} autonomous, {escalations} escalations, {failures} failures → {score}%
   

2. Update marketing/STATUS.md: set last_updated to today's date, preserve all other fields

Step 2: Score Review

Read-only display of the current Autonomy Score with chapter-appropriate context.

Read Data

1. Read marketing/experiment/autonomy-log.md (both Monthly Summary table and System Breakdown sections)
2. Read references/experiment-thesis.md for chapter expectations
3. Parse current and previous month rows from the Monthly Summary table

Display Score

Autonomy Score — {Month Year}

Autonomous decisions:  {N}
Human escalations:     {N}
Agent failures:        {N}
Score:                 {X}%
Trend:                 {up/down/stable} vs last month ({prev_score}%)
Chapter:               {experiment_chapter}

Breakdown by system:
| System | Autonomous | Escalated | Failures |
|--------|-----------|-----------|----------|
| {sys}  | {n}       | {n}       | {n}      |

Chapter Assessment

Compare the score against expected trajectory from references/experiment-thesis.md:

• Chapter 1 (Foundation): Establishing baselines, score expected to be low or undefined
• Chapter 2 (Delegation): Score should start climbing as handoffs happen
• Chapter 3 (Autonomy): Score should be meaningfully high (target 60%+)
• Chapter 4 (Stress Testing): Score may dip as edge cases surface
• Chapter 5 (Verdict): Final measurement

Flag if score is significantly above or below expected range:

Chapter Assessment: {ON TRACK / AHEAD OF EXPECTED / BELOW EXPECTED}
{one-line explanation based on chapter context}

Chapter expectations are soft guidelines, not hard thresholds. The assessment flags deviation but does not alarm — the experiment is exploratory.

Session Log

Append to marketing/logs/{YYYY-MM-DD}.md:

- **Autonomy Tracker** — Score review: {score}% for {YYYY-MM}, {chapter_assessment}

This mode is read-only — no STATUS.md write needed.

Step 3: Trend Analysis

Multi-month view of autonomy score progression with escalation driver analysis.

Read Data

1. Read full marketing/experiment/autonomy-log.md
2. Read marketing/experiment/observations.md (for linking top observations to score changes)

6-Month Rolling Chart

Display an ASCII chart of the most recent 6 months (or all available months if fewer than 6):

Autonomy Score — 6-Month Trend:

Month     | Score | Bar
----------|-------|------------------------------------------
{YYYY-MM} | {n}%  | {'#' * (score / 2)}
{YYYY-MM} | {n}%  | {'#' * (score / 2)}
...

Each # represents 2 percentage points. A score of 60% shows 30 # characters.

Top Escalation Drivers

Aggregate system breakdown data across all tracked months to identify which systems generate the most escalations:

Top Escalation Drivers:
1. {system}: {n} escalations ({pct}% of all escalations)
2. {system}: {n} escalations ({pct}%)
3. {system}: {n} escalations ({pct}%)

Key Observations

Surface the top 3 observations that most influenced the autonomy score. Look in marketing/experiment/observations.md for:

1. Observations with reflections (highest value — they have the "why")
2. Observations of type autonomous-action, human-escalation, or agent-failure
3. Among failures, prioritize highest severity

Key Observations:
- OBS-{NNN} ({date}): {one-line summary} [{type}]
- OBS-{NNN} ({date}): {one-line summary} [{type}]
- OBS-{NNN} ({date}): {one-line summary} [{type}]

Session Log

Append to marketing/logs/{YYYY-MM-DD}.md:

- **Autonomy Tracker** — Trend analysis: {n} months tracked, current score {score}%

This mode is read-only — no STATUS.md write needed.

Reference Table

Mode	References Read	User Files Read	User Files Written
Step 0	references/experiment-thesis.md	MEMORY.md, STATUS.md, experiment/autonomy-log.md	—
Step 1	—	experiment/autonomy-log.md	experiment/autonomy-log.md, STATUS.md, logs/{today}.md
Step 2	references/experiment-thesis.md	experiment/autonomy-log.md	logs/{today}.md
Step 3	—	experiment/autonomy-log.md, experiment/observations.md	logs/{today}.md