log

GrowthOS Observation Logger

Step 0: Detect & Route

Before starting any mode, determine the current state and recommend the next logical 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/observations.md exists. If not, offer to create it from templates/observations.md
5. Check if marketing/experiment/autonomy-log.md exists. If not, create it from templates/autonomy-log.md
6. Read experiment_chapter from STATUS.md frontmatter (default: "Chapter 1: Foundation")
7. Detect observation type from user's message and route to the right step

Slash Command Fast-Path

If invoked via slash command, skip the options menu and go directly to Step 1 (Quick Capture).

Present Options

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

Observation Logger:

Current chapter: {experiment_chapter}
Observations logged: {count from observations.md}
Observations with reflections: {reflected_count}/{total_count}
Current month autonomy score: {score}%

What would you like to do?
1. Quick Capture — log what just happened (under 60 seconds)
2. Reflection — add depth to a recent observation
3. Review — monthly summary with autonomy score

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

Step 1: Quick Capture

Designed for speed — the user should be able to log an observation in under 60 seconds.

Gather Information

Ask only what's needed:

• "What happened?" (1-2 sentences — use the user's words, minimally edited)
• Was this: agent acting autonomously / escalation to human / failure or unexpected outcome? (auto-classify if obvious from context)
• "Significance?" (optional — can be added later via reflection)

Auto-Classify

From the user's answer, classify:

• type: one of autonomous-action, human-escalation, agent-failure, contradiction, milestone
• severity: if failure → low / medium / high (based on impact described)
• system: which agent or system was involved (extract from user's words)

Determine Observation ID

Count existing ### OBS- entries in marketing/experiment/observations.md and increment by 1. Format as OBS-{NNN} with zero-padded three digits (e.g., OBS-001, OBS-012).

Append Entry

Append to marketing/experiment/observations.md:

### OBS-{NNN} — {YYYY-MM-DD}
- **Type:** {type}
- **System:** {system}
- **Chapter:** {experiment_chapter from STATUS.md}
- **Severity:** {severity, if applicable — omit line if not a failure}
- **What happened:** {user's words}
- **Significance:** {user's note, or "—"}
- **Has reflection:** false

Update Autonomy Log

If type is autonomous-action, human-escalation, or agent-failure, update marketing/experiment/autonomy-log.md:

Monthly Summary Table

The Monthly Summary table has 7 columns: Month | Autonomous | Human Escalations | Agent Failures | Total | Score | Notes

1. Find the row for the current month (format: YYYY-MM)
2. If no row exists for the current month, append a new row: | {YYYY-MM} | 0 | 0 | 0 | 0 | 0% | — |
3. Increment the appropriate counter:
   • autonomous-action → increment Autonomous
   • human-escalation → increment Human Escalations
   • agent-failure → increment Agent Failures
4. Recalculate Total: autonomous + human_escalations (agent failures are NOT part of the total)
5. Recalculate Score: autonomous / total * 100 (rounded to nearest integer, format as {score}%)
6. Preserve existing Notes value

System Breakdown

After updating the summary row, update the System Breakdown section for the current month:

1. Look for a ### {YYYY-MM} section under ## System Breakdown
2. If no section exists, create one:

   ### {YYYY-MM}
   
   | System | Autonomous | Escalated | Failures |
   |--------|-----------|-----------|----------|
   | {system} | {n} | {n} | {n} |
   

3. If the section exists, find the row for the {system} from this observation
4. If the system row exists, increment the appropriate counter
5. If the system row does not exist, append a new row for this system

Confirm to User

Show the logged entry back to the user:

Logged OBS-{NNN}:
- Type: {type}
- System: {system}
- What happened: {summary}
{if autonomy-relevant: "Autonomy score updated: {score}% ({autonomous}/{total} decisions this month)"}

Offer Reflection

Immediately after confirming the logged entry, offer type-specific reflection questions while the moment is fresh. This is optional — the user can skip instantly to preserve the under-60-second quick capture path.

1. Ask: "Quick reflection? (skip to move on)"
2. Present 2 questions based on the observation's classified type:

Type	Question 1	Question 2
autonomous-action	"What would have gone wrong without the agent?"	"What did it miss?"
human-escalation	"Could you have given the agent enough context to handle this?"	"Why or why not?"
contradiction	"Which side of the contradiction do you trust more right now?"	"Why?"
milestone	"What's the next milestone this makes possible?"	"What could block it?"
agent-failure	"What should the agent have done instead?"	"Is this a training gap or a fundamental limitation?"

3. If user answers: append a #### Reflection block to the observation entry:

#### Reflection
- **Q:** {question 1}
- **A:** {user's answer}
- **Q:** {question 2}
- **A:** {user's answer}

And update - **Has reflection:** false → - **Has reflection:** true

4. If user says "skip" or equivalent: leave Has reflection: false and proceed to Session Log & State Update (current behavior preserved)

Session Log & State Update

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

   - **Observation Logger** — Logged OBS-{NNN} ({type}): {one-line summary}
   

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

Step 2: Reflection Mode

For adding depth to existing observations. Observations with reflections are the highest-value content sources for future publishable material.

Show Recent Observations

1. Read marketing/experiment/observations.md
2. Skip any observation that already has a #### Reflection block (already reflected via Step 1)
3. Show the last 5 unreflected observations as a numbered list:

   Recent observations:
   1. OBS-{NNN} ({date}) [{type}] — {what happened, truncated to one line}
   2. OBS-{NNN} ({date}) [{type}] — {what happened, truncated to one line}
   ...
   

4. Let the user select one to expand

Prompt for Reflection

Ask the user three questions (can be answered together or one at a time):

1. "What would you have told an enterprise client to do here?" — the conventional advice
2. "What did you actually do?" — the real decision
3. "Why the difference?" — the reasoning behind diverging from conventional wisdom

Append Reflection

Add the reflection to the selected observation entry in marketing/experiment/observations.md. Find the entry by its ### OBS-{NNN} heading and append after the existing fields:

- **Enterprise advice:** {what they'd tell a client}
- **What I actually did:** {what they did}
- **Why the difference:** {reasoning}
- **Has reflection:** true

Update the Has reflection line from false to true.

Confirm to User

Reflection added to OBS-{NNN}.
This observation is now flagged as a content candidate for future publishing.
Observations with reflections: {reflected_count}/{total_count}

Session Log & State Update

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

   - **Observation Logger** — Added reflection to OBS-{NNN}
   

2. Update marketing/STATUS.md: set last_updated to today's date

Step 3: Review Mode

Monthly summary of observations and autonomy progress. This is read-only — no files are written except the session log.

Gather Data

1. Read marketing/experiment/observations.md
2. Read marketing/experiment/autonomy-log.md
3. Filter observations for the current month (match date in ### OBS-{NNN} — {YYYY-MM-DD} headings)

Present Monthly Summary

Monthly Observation Summary — {YYYY-MM}:

| Type                 | Count |
|----------------------|-------|
| Autonomous Actions   | {n}   |
| Human Escalations    | {n}   |
| Agent Failures       | {n}   |
| Contradictions       | {n}   |
| Milestones           | {n}   |
| TOTAL                | {n}   |

Autonomy Score: {score}% ({autonomous} autonomous / {total} total decisions)
Observations with reflections: {reflected_count}/{total_count} ({percent}%)

List Observations by Type

Group observations for the current month by type and list each:

Autonomous Actions:
- OBS-{NNN} ({date}): {one-line summary} {if has_reflection: "[has reflection]"}

Human Escalations:
- OBS-{NNN} ({date}): {one-line summary} {if has_reflection: "[has reflection]"}

...

Highlight Content Candidates

If any observations have reflections, highlight them:

Content Candidates (observations with reflections):
- OBS-{NNN}: {what happened} → {enterprise advice vs. actual decision, one line}

These are the highest-value entries for future narrative content about the experiment.

Session Log

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

- **Observation Logger** — Monthly review for {YYYY-MM}: {total_count} observations, {score}% autonomy score

Reference Table

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