An intelligent next-step engine that filters agency tasks through a 93% viability bar to ensure high-impact execution.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install 93pct
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install 93pct using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is 93pct Agency Autocomplete?
93pct acts as a strategic autocomplete for agency workflows, functioning much like a search engine's predictive text but for project management and execution. It leverages Shannon entropy theory to distinguish high-value information signals from noise, ensuring that every suggested action is concrete and viable.
By integrating this tool into your Openclaw Skills library, you can eliminate decision fatigue and focus exclusively on tasks with the highest ROI-to-effort ratio. The skill is built on the doctrine of routing all decisions through information value (Shannon) to reach execution hubs (Penn Station), effectively reducing operational entropy.
93pct Agency Autocomplete Use Cases
- Determining the most effective immediate action during complex project transitions.
- Auditing task backlogs to identify and prioritize items with the highest information density.
- Managing a job approval stack for streamlined agency execution.
- Reducing operational entropy by filtering out vague or non-viable suggestions.
How 93pct Agency Autocomplete Works
- The system analyzes current context and available metadata to identify potential next steps.
- Each potential action is evaluated against the 93% bar for concreteness and immediate viability.
- A Shannon score is assigned to measure the information density and signal-to-noise ratio.
- Tasks are ranked based on their ROI vs. effort, generating a unique Job ID for approval.
- Users execute or mark tasks as completed via the CLI to update the operational stack.
93pct Agency Autocomplete Setup
To integrate this tool into your workflow, ensure it is located within your Openclaw Skills directory and use the following commands:
# Generate the top 5 concrete next steps
python3 /root/.openclaw/workspace/skills/93pct/suggest.py
# View the current approval stack
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --stack
# Mark a specific job as completed
python3 /root/.openclaw/workspace/skills/93pct/suggest.py --done <id>
93pct Agency Autocomplete Data Schema & Taxonomy
The skill utilizes a structured output format to quantify task value and execution requirements. Every suggestion follows this schema:
| Attribute | Description |
|---|---|
| Shannon Score | A 0-10 scale measuring information density and signal strength. |
| Effort | The estimated time in minutes required to complete the task. |
| Blocker | Identification of any dependencies or obstacles to immediate action. |
| Job ID | A unique identifier required for tracking and approval. |
| Command | The exact action or CLI command to be executed. |
93pct Agency Autocomplete Advanced Features
- ROI-to-Effort Ranking: Automatically prioritizes tasks that deliver the most value for the least work.
- The 93% Standard: A rigorous filtering mechanism that rejects any suggestion that is not concrete, viable, or measurable.
- Shannon Signal Processing: Advanced information theory application to ensure only high-signal actions are presented.
- Approval Stack Management: A built-in system to track and execute high-priority job IDs efficiently.
SKILL.md
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