Signal-First is a response calibration protocol that forces Claude to match answer depth to question complexity, prioritizing information density over verbosity.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install signal-first
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 signal-first 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 Signal-First?
Signal-First addresses one of the most common frustrations in AI interaction: the tendency for LLMs to over-explain simple concepts. By implementing a strict signal-to-noise ratio, this skill ensures that a ten-word question receives a concise answer rather than a ten-paragraph essay. It transforms AI output from a wordy, conversational assistant into a high-density information engine.
Built for the Openclaw Skills ecosystem, this protocol focuses on deleting 'throat-clearing' phrases, restatements, and unnecessary summaries. It forces the model to evaluate the complexity of a request before drafting, ensuring the final output is proportional to the user's actual needs.
Signal-First Use Cases
- Reducing AI verbosity for simple factual lookups and yes/no questions.
- Streamlining code generation by removing obvious explanations and narrative wrappers.
- Improving focus during complex analysis by using structured headers only when necessary.
- Eliminating repetitive pleasantries and repetitive restatements in long-running threads.
How Signal-First Works
- Request Classification: The skill silently categorizes the incoming prompt by type (lookup, task, analysis) and complexity (trivial to complex).
- Target Setting: Based on classification, it sets a target length and format, ranging from a single-line response to a structured 600+ word deep dive.
- Draft and Compress: The response is drafted and then put through a compression pass to remove setup sentences, trailing offers, and caveats.
- Density Check: A final internal audit evaluates the ratio of useful content to total words before the output is displayed.
Signal-First Setup
To add Signal-First to your environment, use the following commands within your CLI:
openclaw install signal
# Recommended pairings for better output
openclaw install clarity-first
openclaw install honest-critic
Signal-First Data Schema & Taxonomy
Signal-First utilizes a Calibration Scale to organize output formatting and metadata taxonomy:
| Request Type | Target Length | Format Style |
|---|---|---|
| Yes/No | 1 sentence | Plain text |
| Factual | 1-2 sentences | Plain text |
| Short Task | < 100 words | Minimal Markdown |
| Medium Task | 100-300 words | Structured (if helpful) |
| Complex | 300-600 words | Headers + Full Structure |
| Systemic | 600+ words | Full structure, high density |
Signal-First Advanced Features
- Zero-Framing Mode: For short responses, the skill enables an output mode with no intro or outro text.
- Multi-Skill Synergy: Specifically designed to work with clarity-first and honest-critic for high-integrity, concise communication.
- Pass-through Compression: Automated pass to merge redundant bullet points and delete hedge-stacking language.
- Format Logic: Context-aware formatting that switches between tables, prose, and numbered steps based on the data type.
SKILL.md
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