93pct
Autocomplete for agency next steps. Like Google autocomplete but for what to do next. Given any context, returns the top concrete viable actions ranked by ROI/effort ratio. Always outputs exactly one job ID to approve. Named after the 93% standard — every suggestion must clear that bar.
Source facts
- Repository
- RabbitAI-Lab/rabbit-plugins-upstream
- Last source activity
- July 26, 2026 at 20:50
- Detected SKILL.md language
- English
- Stars
- 0
- Forks
- 0
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Source instructions · Read-only preview- name
- 93pct
- description
- Autocomplete for agency next steps. Like Google autocomplete but for what to do next. Given any context, returns the top concrete viable actions ranked by ROI/effort ratio. Always outputs exactly one job ID to approve. Named after the 93% standard — every suggestion must clear that bar.
- version
- 1.0.0
- author
- Fiesta
- tags
- ["planning","autocomplete","next-steps","agency","productivity"]
# 93% — Agency Autocomplete
## Doctrine
> "Plan Shannon → Penn Station"
Shannon is the currency of information (Claude Shannon, entropy theory).
Penn Station is the commuter hub — where everything converges.
The plan: route all decisions through Shannon (information value) to reach the station (execution).
Low Shannon = entropy = noise = waste.
High Shannon = signal = viable next step.
## Usage
```
python3 /root/.openclaw/workspace/skills/93pct/suggest.py # top 5 next steps now
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --stack # show approval stack
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --done <id> # mark completed
```
## Output format
Each suggestion includes:
- Shannon score (0-10, information density)
- Effort (minutes)
- Blocker (what stops it)
- Job ID to approve (if exec needed)
- Exact command or action
## The 93% Bar
A suggestion clears 93% if:
- It is concrete (not "consider doing X")
- It is viable right now (blocker is known and solvable)
- It produces measurable output
- It costs less than it returns
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