self-improve

Interpret vague user requests into structured intent with traceable findings.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/andrey-belen/alto-iam-cloud --skill self-improve-andrey-belen
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: self-improve
Source: https://github.com/andrey-belen/alto-iam-cloud/tree/main/.claude/skills/self-improve
Command: npx skills add https://github.com/andrey-belen/alto-iam-cloud --skill self-improve-andrey-belen

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transforms vague user requests into enriched, traceable descriptions to support agent generation and context-driven decision making.

Core Features & Use Cases

  • Interpret ambiguous intent: extract action, subject, and implicit assumptions.
  • Synthesize findings with source attribution for traceability.
  • Assess complexity and flag issues for deeper analysis.

Quick Start

Provide a user request to the skill and receive a structured interpretation including Intent and Findings.

Frequently Asked Questions about self-improve

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I interpret vague user requests into structured project context?

To interpret vague user requests, extract the core action, subject, and implicit assumptions to synthesize findings with source attribution. This transforms ambiguous intent into structured, traceable descriptions for project planning.

What is the best way to synthesize insights from available project context?

The best way to synthesize insights from project context is to assess complexity based on scope, conflicts, and trade-offs while attributing findings to sources. This ensures traceability and flags issues for deeper analysis.

How do I prepare context for agent generation from ambiguous intents?

You prepare context for agent generation by transforming ambiguous intents into enriched, traceable descriptions. The process requires extracting implicit assumptions and synthesizing findings with source attribution.

Can I assess project complexity and flag issues from a simple text request?

Yes, you can assess complexity and flag issues by evaluating scope, conflicts, and trade-offs extracted from the request. The interpretation process outputs structured intent and synthesized findings to highlight areas needing deeper analysis.

Does this approach work for clarifying ambiguous intent during project planning?

Yes, clarifying ambiguous intent during project planning is a core application. It transforms vague user requests into structured intent with traceable findings, directly supporting context-driven decision making.