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Claude Code: AI Agent Workflow Collection

Skill pack
9 skills0 selected
dazzlemlSkills in this pack

Run an N-round expert consultation with one of our own sub-agents (default: brainstorm) that has repo access -- like collaborate3, but the consultant can read the code, trace design docs, and run real tests. Spawn once, continue via SendMessage each round; saves 2N+1 verbatim round files plus an independent dev-workflow final assessment. N defaults to 3.

English

Initiates a structured analysis of a problem using the DEV WORKFLOW PROCESS with specific contextual guidance.

English

Rebuild project context at session start by reading key docs, git state, issues, and design history. Accepts an optional argument describing the current focus or goal.

English

Initialize standard GitHub issues (1 Roadmap, 2 Quick Notes) with the canonical label set for a new project.

English

Read-only pre-merge review. Lists dual-touched files, shows OURS / THEIRS / merge-base diffs, and flags likely-collision patterns so the integrator understands the full scope before running git merge. Accepts a target branch (default: main).

English

Set up a new project using DazzleTools git-repokit-template and git-repokit-common. Creates repo, adds subtree, initializes standard structure.

English

Produce a hand-runnable human test checklist alongside automated tests. Run after writing automated test suites for a phase/feature that ships user-visible behavior. Creates a markdown doc (public by default in tests/checklists/, or in a project-private location for sensitive content) that a human walks through to verify end-to-end behavior that mocks can't cover -- shell rendering, Windows codepages, real subprocess behavior, interactive prompts, file atomicity under real conditions, config isolation, and other "the mocks say it works but does it REALLY" scenarios.

English

Inbound context recovery: find existing WhereWeAre docs, postmortems, issues, and git state to answer 'what's going on in this project?' Companion to /whereweare (which writes snapshots).

English

Forward-looking project snapshot: what was done, what's next, key files, open issues, related projects, and everything needed to resume work after time away.

English

Includes Collab N Local, Dev Workflow Process, Familiarize, and other workflows.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Pack stats

Skills9CategorygeneralStars0

What’s included

Collab N Local

Run an N-round expert consultation with one of our own sub-agents (default: brainstorm) that has repo access -- like collaborate3, but the consultant can read the code, trace design docs, and run real tests. Spawn once, continue via SendMessage each round; saves 2N+1 verbatim round files plus an independent dev-workflow final assessment. N defaults to 3.

Dev Workflow Process

Initiates a structured analysis of a problem using the DEV WORKFLOW PROCESS with specific contextual guidance.

Familiarize

Rebuild project context at session start by reading key docs, git state, issues, and design history. Accepts an optional argument describing the current focus or goal.

GitHub Issues Setup

Initialize standard GitHub issues (1 Roadmap, 2 Quick Notes) with the canonical label set for a new project.

Merge 3 Way Split

Read-only pre-merge review. Lists dual-touched files, shows OURS / THEIRS / merge-base diffs, and flags likely-collision patterns so the integrator understands the full scope before running git merge. Accepts a target branch (default: main).

Repokit Setup

Set up a new project using DazzleTools git-repokit-template and git-repokit-common. Creates repo, adds subtree, initializes standard structure.

Test Checklist

Produce a hand-runnable human test checklist alongside automated tests. Run after writing automated test suites for a phase/feature that ships user-visible behavior. Creates a markdown doc (public by default in tests/checklists/, or in a project-private location for sensitive content) that a human walks through to verify end-to-end behavior that mocks can't cover -- shell rendering, Windows codepages, real subprocess behavior, interactive prompts, file atomicity under real conditions, config isolation, and other "the mocks say it works but does it REALLY" scenarios.

Wherearewe

Inbound context recovery: find existing WhereWeAre docs, postmortems, issues, and git state to answer 'what's going on in this project?' Companion to /whereweare (which writes snapshots).

Whereweare

Forward-looking project snapshot: what was done, what's next, key files, open issues, related projects, and everything needed to resume work after time away.

Quick start

  1. Choose your skills. Select individual skills above, or choose the entire pack.
  2. Copy the install prompt. Use Copy install prompt above the list.
  3. Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.

Try it with your agent

After installation, start with a request like:

Example request
Use the Collab N Local skill to help with my task.
Ask me for the context you need before getting started.

Requirements & license

  • A coding agent that can access your project files and install skills.
  • Your agent checks each skill’s instructions, dependencies, and permissions during setup.
  • Reported license for the skills shown: GPL-3.0. The author’s terms apply.
Claude Code: AI Agent Workflow Collection | Agent Skills Atlas