ai-productivity
High-speed intake for shaping vague prompts, triaging complex tasks, and compressing context for efficient execution.
skill install https://www.promptspace.in/skills/ai-productivityWhat it does
The AI Productivity skill acts as a high-performance intake layer for your agentic workflows. It identifies and resolves common execution bottlenecks before they waste tokens or time: vague prompts, overwhelming context "bloat," and high-risk ambiguous requests. Instead of diving blindly into a task, this skill triages the work, compresses relevant data, or rewrites instructions into actionable prompts.
Why use this skill
Prompting an AI is easy; getting a complex agent to execute a multi-step task without drifting is hard. This skill is better than manual prompting because it applies consistent logic to "shape" a request. It prevents the "walls of text" problem by extracting only pertinent facts and decisions, and it stops execution errors by forcing success criteria on vague goals. It ensures that when a task is handed off to specialized tools or other agents, they receive a high-signal, low-noise brief.
Supported workflows
- Request Triage: Scopes risky or broad tasks before execution starts.
- Context Compression: Distills long session logs into facts, decisions, and next steps.
- Lightweight Rewriting: Converts "fuzzy" ideas into structured prompts with clear constraints.
- Agent Handoffs: Generates standardized briefs for multi-agent systems via the multi-agent-coordinator.
The Output
Depending on the input, you receive a direct answer, a structured internal brief (Summary, Decisions, Open Questions), or a refined prompt ready for immediate execution, complete with success criteria and formatting rules.
Use cases
- Refine vague user requests into actionable, high-precision prompts sworns
- Filter redundant context to reduce token usage and improve model accuracy
- Triage complex multi-step workflows to ensure logical task execution
- Mitigate execution errors by identifying high-risk or ambiguous instructions
Example
Prompt
Output
### Rewritten Prompt Context: Debugging intermittent API timeout. Goal: Identify root cause in logs. Constraints: Focus on 'auth-service' headers. Success Criteria: List of 3 likely failure points with timestamps. Output format: Technical bulleted list.
Known limitations
- Not a replacement for complex project management or deep prompt engineering. - May overlook subtle nuances if context compression is applied too aggressively to technical data.