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J0Jng
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to-spec

Synthesizes conversation context into a structured spec published to the project issue tracker.

7|1|Updated Jul 17, 2026
Search Tags:#planning#issue tracker#user stories#spec#prd#product requirements#triage
One-click install
npx skills add https://github.com/J0Jng/MathModelingAgents --skill to-spec-j0jng
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: to-spec
Source: https://github.com/J0Jng/MathModelingAgents/tree/main/.claude/skills/engineering/to-spec
Command: npx skills add https://github.com/J0Jng/MathModelingAgents --skill to-spec-j0jng

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Turning a long design discussion into a formal spec (PRD) is tedious and often requires re-interviewing stakeholders. This Skill converts the current conversation and codebase understanding directly into a structured spec and publishes it to the project issue tracker without asking redundant questions. ## Core Features & Use Cases - Conversation-to-Spec Synthesis: Generates a complete spec from existing discussion context, with no interview phase. - Test Seam Planning: Identifies and proposes testing seams in the codebase, preferring existing high-level seams, and confirms them with the user. - Issue Tracker Publishing: Writes the spec using a fixed template (problem statement, user stories, implementation and testing decisions, scope) and publishes it with a ready-for-agent triage label. - Use Case: After discussing a new feature with the AI, invoke this Skill to produce a ready-for-development spec ticket covering user stories, architectural decisions, and out-of-scope items. ## Quick Start Ask the AI to turn the current conversation into a spec and publish it to the project issue tracker.

Frequently Asked Questions about to-spec

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

FAQPage Schema
How do I turn a conversation into a product spec?▼

Invoke the to-spec skill after discussing the feature. It synthesizes the existing conversation and codebase context into a structured spec with problem statement, user stories, and implementation decisions, then publishes it to the issue tracker.

Does the to-spec skill interview the user before writing the spec?▼

No. The skill explicitly avoids interviewing and only synthesizes what has already been discussed. The one exception is confirming proposed testing seams with the user before writing the spec.

What sections does the generated spec template include?▼

The template includes Problem Statement, Solution, User Stories, Implementation Decisions, Testing Decisions, Out of Scope, and Further Notes. It avoids specific file paths and code snippets except for decision-rich prototype fragments.

What setup is required before using this skill?▼

The issue tracker and triage label vocabulary must be configured first, via the /setup-matt-pocock-skills command. Without it, the skill cannot publish the spec or apply the ready-for-agent triage label.

Can this skill be invoked automatically by the AI?▼

No. The skill sets disable-model-invocation and its policy disallows implicit invocation, so it only runs when the user explicitly requests it.

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