Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    Signal-to-Spec Translator

    2

    Transform vague feedback and messy signals into rigorous, execution-ready technical specifications.

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    Signal-to-Spec Translator

    Signal-to-Spec Translator

    Example session with this skill installed

    Users are saying the onboarding flow feels 'clunky' and some are dropping off at the credit card screen. We should probably add Apple Pay or maybe just simplify the labels.

    • Read your context and instructions
    • Compiled the signal-to-spec translator
    • Generated the UI component

    TRANSLATED SPEC

    • Objective: Reduce friction in the payment step of onboarding.
    • Target Actor: New trial users.
    • In-Scope: Payment method expansion (Apple Pay), Label audit.
    • Success Criteria: 15% increase in conversion from 'Billing' to 'Success' page.
    • Build-Readiness: Partially Ready.

    signal-to-spec-translator.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Convert fragmented user complaints into structured product requirements.Audit stakeholder requests for hidden assumptions and high-risk gaps.Translate vague 'AI needs' into specific behavior and constraint specs.Evaluate if a request is 'Build-Ready' or requires further discovery.

    About this skill

    What it does

    The Signal-to-Spec Translator is a high-discipline framework designed to bridge the gap between messy, real-world inputs and execution-grade technical specifications. It takes vague requests, fragmented feedback, and "signal clouds"—like 'users are confused' or 'we need an AI feature'—and systematically decomposes them into structured, buildable artifacts.

    Why use this skill

    Most development waste happens before a single line of code is written, caused by building from unprocessed signals. This skill moves beyond simple paraphrasing; it identifies raw signal types, surfaces hidden assumptions, separates observation from interpretation, and maps specification gaps. It prevents "premature solutioning" by highlighting what is not yet ready for implementation.

    What the output looks like

    Rather than a simple summary, you receive a professional intermediary artifact. This includes a Signal Field analysis, a Decomposition of signal units with confidence levels, an Assumption Load audit, and finally, a Translated Spec featuring objectives, constraints, and success criteria. It concludes with a Build-Readiness Check and a warning on what not to build yet.

    Supported Workflows

    • Product Requirement Documents (PRDs)
    • AI Behavior & Agent Specifications
    • Automation & Internal Tool Briefs
    • Experiment Design & Evaluation Rubrics

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Recently published to Agensi

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    Security scanned

    Verified clean 3 months ago

    • Passed all security checks, Safe to install

    Listed3 months ago

    What's inside

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