Skill: Intake

Normalize raw work requests into structured intake_output JSON artifacts.

2|Updated Apr 26, 2026
One-click install
npx skills add https://github.com/anderson-joyle/claude-a-team --skill skill-intake
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Skill: Intake
Source: https://github.com/anderson-joyle/claude-a-team/tree/main/skills/intake
Command: npx skills add https://github.com/anderson-joyle/claude-a-team --skill skill-intake

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents downstream misunderstandings by turning raw, inconsistent work requests into a structured, evidence-aware intake artifact that the rest of the workflow can trust.

Core Features & Use Cases

  • Request normalization: Converts raw demand plus runtime envelope inputs into a consistent internal representation, including derived titles/names.
  • Evidence preservation: Keeps request constraints, evidence paths, and tracking references intact for auditable, stage-by-stage processing.
  • Routing suggestions: Recommends which later gates (like Architect/Security/Review/Release Readiness) should run based on what the request requires.

Quick Start

Use the /intake skill to normalize a new engineering work request by providing its raw demand and the runtime request envelope so it can emit a single intake_output JSON artifact.

Frequently Asked Questions about Skill: Intake

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

FAQPage Schema
How do I normalize raw work requests into structured JSON artifacts for workflow orchestration?

To normalize raw work requests, you apply an intake process that converts inconsistent demand and runtime envelope inputs into a typed JSON artifact with derived titles, preserving evidence paths and tracking references for reliable downstream processing.

What is request normalization for engineering intake and why is it needed?

Request normalization is the process of structuring raw demand into a consistent internal representation. It is needed to prevent downstream misunderstandings by ensuring every engineering or architectural decision relies on a consistent, evidence-aware intake artifact.

How does evidence preservation work during intake request normalization?

Evidence preservation works by keeping original request constraints, evidence paths, and tracking references intact within the emitted JSON artifact. This ensures auditable, stage-by-stage processing as the workflow progresses through subsequent routing gates.

Can I get routing recommendations for architectural and security gates from an intake artifact?

Yes, the normalized intake artifact provides routing suggestions that recommend which later gates, such as Architect, Security, Review, or Release Readiness, should execute next based on what the specific engineering request requires.

Do I need to provide a runtime envelope to classify a new engineering request?

Yes, you need to provide the raw demand along with the runtime request envelope. The intake process uses both to emit a single structured intake_output JSON artifact and asks only blocking questions required for accurate classification.