Develop Team logo

Develop Team

Community
EricTechPro
develop-team

This skill should be used when the user asks to "develop a feature", "implement a ticket", "build PROJ-123", "run the development pipeline", "develop this ticket end to end", or wants fully autonomous feature implementation with parallel research agents, planning, phased implementation, review, and PR creation. Zero checkpoints; pauses only on blockers.

Overview

PublisherEricTechPro
Repositorystartup-claude-skills
Skill namedevelop-team
Stars
59
Forks
17
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by EricTechPro on GitHub. Read the source before you install it.

Installation

Install the Develop Team AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/EricTechPro/startup-claude-skills/tree/main/skills/develop-team
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/EricTechPro/startup-claude-skills.git /tmp/startup-claude-skills
mkdir -p .claude/skills
cp -r /tmp/startup-claude-skills/skills/develop-team .claude/skills/develop-team
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Develop Team in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Develop Team on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Develop Team is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Develop Team

Orchestrate a full feature development cycle using parallel sub-agents. Takes a ticket reference or freeform task and drives it through deep research, planning (with design/test/migration specs), implementation with per-phase test generation, review, and automatic PR creation — fully autonomous with no checkpoints unless a genuine blocker is detected.

When to Use This Skill

  • Starting a new feature - Hand off a ticket and let the pipeline research, plan, and implement
  • Exploring before implementing - Use plan-only=true to get a researched plan without writing code
  • Structured development - Parallel research + review instead of ad-hoc implementation

Parameters

ParameterDefaultDescription
typeautoFeature type: auto|ui-heavy|full-stack|backend-only|async-heavy
auto-committrueCreate atomic commits after each implementation phase
skip-reviewfalseSkip refactor and review phases
skip-testsfalseSkip per-phase test generation
skip-prfalseSkip automatic PR creation
skip-migrationsfalseSkip DB migration analysis and application
plan-onlyfalseStop after planning (no implementation)

Invocation

/develop-team PROJ-123
/develop-team PROJ-123 plan-only=true
/develop-team "Add currency preferences to user settings"
/develop-team PROJ-45 auto-commit=false skip-review=true
/develop-team PROJ-67 type=ui-heavy
/develop-team PROJ-89 type=backend-only skip-tests=true skip-pr=true

Prerequisites

This skill expects the following project conventions:

  1. CLAUDE.md at project root — defines coding standards, patterns, folder structure, and conventions
  2. Ticket system (optional) — Jira MCP or similar for fetching ticket details
  3. Spec/backlog location — configurable; defaults to searching common locations (/backlog/, /specs/, /docs/specs/)
  4. Companion skills (optional) — /refactor and /review-fix for Phases 5-6. If not available, those phases are skipped gracefully.

Architecture

ORCHESTRATOR (main session - manages state, cross-references outputs)
|
+-- Phase 0: INIT — parse input, create state, determine ticket vs freeform
|
+-- Phase 1: CONTEXT + CLASSIFY + DB PRE-SCAN
|   Ticket (MCP or manual) + spec file + git state
|   Past-ticket context (git log, gh pr list)
|   DB schema pre-scan (if DB tools available, scan related tables)
|   Classify: ui-heavy | full-stack | backend-only | async-heavy
|
+-- Phase 2: RESEARCH (4-6 parallel agents, run_in_background: true)
|   Agent 1: Deep Codebase Explorer    (system-architect)          [always]
|   Agent 2: CLAUDE.md Compliance Mapper (code-refactorer)         [always]
|   Agent 3: Requirements Mapper       (product-strategy-advisor)  [always]
|   Agent 4: Design System Integrator  (premium-ux-designer)       [if ui-heavy|full-stack]
|   Agent 5: Async Flow Analyzer       (system-architect)          [if async-heavy]
|   Agent 6: DB Migration Analyzer     (system-architect)          [if DB changes needed]
|   (auto-proceed — pause only on blockers)
|
+-- Phase 3: PLANNING — synthesize into plan + design spec + test plan + migration plan
|   (auto-proceed — plan-only=true pauses here)
|
+-- Phase 4: IMPLEMENTATION — per-phase: agent spawn → build/lint → tests → commit
|   UI phases → premium-ux-designer | Backend → general-purpose
|
+-- Phase 4.5: DB MIGRATIONS — apply via migration tooling, save locally
+-- Phase 5: REFACTOR → /refactor scope=session max-iterations=1 auto-fix=true
+-- Phase 6: REVIEW → /review-fix max-iterations=2 auto-commit={inherited}
+-- Phase 7: PR CREATION → gh pr create with full summary
+-- Phase 8: SYNTHESIS — report with commits, tests, migrations, PR link
|
+-- STATE: .develop-team/state.json

Workflow

Phase 0: Initialize

  1. Parse $ARGUMENTS: ticket reference (pattern: {PROJECT_KEY}-\d+, e.g. PROJ-123) or freeform task description
  2. Parse parameters: type, auto-commit, skip-review, skip-tests, skip-pr, skip-migrations, plan-only
  3. Create .develop-team/ directory if needed
  4. Check for existing state.json — if found, offer to resume from last completed phase
  5. Initialize state file

State file at .develop-team/state.json: See references/state-schema.md for full schema and backward compatibility notes.

Phase 1: Gather Context + Classify Feature Type

If ticket reference:

Fetch ticket details using the project's configured ticket system (Jira MCP, GitHub Issues, Linear, etc.):

Extract: key, summary, description, acceptance criteria,
         status, issue type, priority, labels
Find spec file:

Search common spec/backlog locations for files matching ticket number or feature name. Typical locations:

  • /backlog/ (organized by version or priority)
  • /specs/
  • /docs/specs/
  • Custom location defined in CLAUDE.md

Read spec for requirements, user stories, success criteria.

Past-Ticket Context

Load context from previous related work to avoid re-discovering solved problems:

bash
git log --oneline --all --grep="{ticketKey}" -20
gh pr list --state all --search "{ticketKey}" --json number,title,state,mergedAt --limit 5

Store summary of past PRs and patterns learned in state.json.pastTicketContext.

DB Schema Pre-Scan

If ticket mentions database tables/schema/data model, query the project's database tooling for schema information: table names, columns, policies, indexes. Feeds into Agent 6.

Git state:
bash
git branch --show-current && git status --short && git log --oneline -5
Branch Creation (ticket references only)

When input is a ticket reference, create a feature branch off the current branch:

bash
# Extract ticket number and kebab-case summary
# PROJ-111 + "Add currency preferences" → 111-add-currency-preferences
git checkout -b {ticketNumber}-{kebab-case-summary}

Store branch name in state.json.branchName. Skip for freeform tasks (user is already on their working branch).

Classify Feature Type

If type != auto, use directly. Otherwise, scan combined ticket text for keyword signals:

Feature TypeKeyword Signals
ui-heavycomponent, page, dialog, form, modal, sheet, table, dashboard, responsive, layout, sidebar, nav, tab, wizard
backend-onlymigration, RLS, API route, cron, webhook, edge function, schema, index, policy, trigger (without UI keywords)
async-heavyqueue, cron, background, batch, import, export, process, job, polling, retry, state machine, pipeline
full-stackMix of signals or neither dominates (default fallback)

Logic: UI > 2x backend → ui-heavy. Backend > 2x UI and UI=0 → backend-only. Async >= 2 → async-heavy. Else → full-stack.

Phase 2: Research (4-6 Parallel Sub-Agents)

Spawn all applicable agents with run_in_background: true. Each receives ticket context, spec file, and past-ticket context.

AgentSub-Agent TypeConditionReturns
Deep Codebase Explorersystem-architectAlwaysFile map, data flow chains, exact imports
CLAUDE.md Compliance Mappercode-refactorerAlwaysPer-file-type rule cards, golden references
Requirements Mapperproduct-strategy-advisorAlwaysPhases, tasks, test plan, migration plan
Design System Integratorpremium-ux-designerui-heavy/full-stackComponent hierarchy, exact design tokens, all states
Async Flow Analyzersystem-architectasync-heavyState machine, race conditions
DB Migration Analyzersystem-architectDB changes neededSchema diff, ready SQL, policies

For full agent prompts, read references/agent-prompts.md.

Post-Research: Auto-Proceed with Blocker Detection

Collect results via TaskOutput. Auto-proceed UNLESS a blocker is detected.

Blockers (pause and ask user only if):

  • Research agents recommend incompatible approaches
  • Feature requires tables with no migration plan to create them
  • Acceptance criteria are ambiguous or contradictory
  • A research agent completely failed (total failure, not just partial)

If no blockers, log summary and proceed directly:

Research complete ({N} agents, 0 blockers)
  Codebase Explorer: {N} files, {N} flow chains | Compliance Mapper: {N} rule cards
  Requirements Mapper: {N} phases, {N} tasks | Design/Async/Migration: {status}
Proceeding to planning...

Phase 3: Planning (Inline)

The orchestrator synthesizes all research into a cohesive plan. Done inline (not sub-agent) to cross-reference multiple outputs.

Cross-reference: Codebase Explorer's file map + Compliance Mapper's rule cards + Requirements Mapper's phases + Design System Integrator's specs (if ran) + Async Analyzer (if ran) + DB Migration Analyzer (if ran).

Plan structure: Save to .develop-team/plan.md. See references/plan-template.md for the full template. Includes: context, per-phase tasks with convention notes, design specification (if UI), test plan, migration plan, AC coverage, and files summary.

Save design spec to state.json.designSpec. If plan-only=true, present plan and stop. Otherwise auto-proceed.

Phase 4: Implementation

Execute plan phase by phase:

1. Select agent:

Phase ContentAgent Type
Files match components/** or page/view files, type is ui-heavy/full-stackpremium-ux-designer
All other phasesgeneral-purpose

2. Spawn agent (run_in_background: false):

For UI phases → premium-ux-designer:

Implement Phase {N}. Follow the design specification EXACTLY — do not improvise colors/shadows/spacing.

## Phase Tasks: {tasks from plan}
## Design Specification: {full design spec — hierarchy, tokens, states, responsive}
## Convention Rules: {component rule card from Compliance Mapper}
## Anti-Slop Checklist: {from Design System Integrator}

Instructions: Implement tasks in order. Run build and lint commands after. Do NOT implement other phases.

For non-UI phases → general-purpose:

Implement Phase {N}.

## Phase Tasks: {tasks from plan}
## Convention Rules: {relevant rule cards — api-route, service, schema, store}
## Async Analysis: {if applicable, from Async Flow Analyzer}

Instructions: Implement tasks in order. Run build and lint commands after. Do NOT implement other phases.

3. Verify: Run build and lint commands (per CLAUDE.md configuration). If fails: spawn debug agent. If still fails after 2 attempts, stop.

4. Generate tests (unless skip-tests=true): Spawn general-purpose with test cases from the plan for this phase. Run test command. Update state.json.tests.perPhase.

5. Commit (if auto-commit=true): create atomic commit with phase name and files list.

6. Update state and proceed to next phase.

Phase 4.5: DB Migrations (Conditional)

Skip if: skip-migrations=true OR no migrations planned.

For each migration in the plan:

  1. Apply: Use the project's migration tooling (Supabase MCP, Prisma, Drizzle, raw SQL, etc.)
  2. Save locally (CRITICAL): Save migration file to the project's migrations directory following existing naming conventions
  3. Update related files: Edit any select/query builder files, ORM schemas, or type definitions as specified in the plan
  4. Commit if auto-commit enabled

On migration failure: Save SQL to .develop-team/failed-migration.sql, ask user: skip or stop.

Phase 5: Refactor (Companion Skill Delegation)

Skip if skip-review=true or /refactor skill not available. Invoke: /refactor scope=session max-iterations=1 auto-fix=true

After: read .refactor/state.json, update state, clean up .refactor/.

Phase 6: Review (Companion Skill Delegation)

Skip if skip-review=true or /review-fix skill not available. Invoke: /review-fix max-iterations=2 auto-commit={inherited}

After: read .review-fix/state.json, update state, clean up .review-fix/.

Phase 7: PR Creation

Skip if: skip-pr=true.

bash
gh pr create --title "{type}({scope}): {summary} ({ticket key})" --body "$(cat <<'EOF'
## Summary
{1-3 bullets from ticket}

## Changes
{Phases implemented with key files}

## Test Plan
| Phase | Tests | Passed | Failed |
{from state.json.tests.perPhase}
- [ ] Build passes
- [ ] Lint passes

## Database Migrations
{List of migrations applied, or "None"}

## Acceptance Criteria
| Criterion | Status |
{from plan}

## Ticket
{ticket key}: {URL if available}

---
Generated with [Claude Code](https://claude.com/claude-code) via /develop-team
EOF
)"

Update state.json.pullRequest. On failure: save body to .develop-team/pr-body.md, note in synthesis.

Phase 8: Synthesis

markdown
# Development Complete: {Ticket Key} - {Summary}

## Summary
| Metric | Value |
|--------|-------|
| Feature type | {featureType} |
| Phases implemented | {N} |
| Total commits | {N} |
| Tests | {N} generated ({N} passed, {N} failed) |
| Migrations | {N} applied |
| Refactor | {N} fixed, {N} strategic |
| Review | {N} iterations, {N} fixed |
| Pull request | {PR URL or "Skipped"} |

## Commits — {all with hashes}
## Acceptance Criteria — {criterion → status}
## Test Summary — {per-phase results}
## Database Migrations — {migration → status → local file}
## Files Changed — {action → path}
## Next Steps — {merge PR, remaining items, manual testing}

Update state.json with status: "completed".


State File Reference

Location: .develop-team/state.json — enables resumability.

If existing state found, ask user: "Resume from Phase {N+1}" or "Start fresh".


Error Handling

ScenarioAction
Ticket fetch failureAsk user for details manually, don't block
Research agent failureContinue with other agents, note gap
Build/lint failureDebug agent x2, then stop and report
Implementation agent failureSave to state, report, offer resume
Test failureLog but don't block — may resolve in later phases
Migration failureSave SQL to .develop-team/failed-migration.sql, ask skip/stop
PR creation failureSave body to .develop-team/pr-body.md, continue to synthesis
/refactor not availableLog, skip to Phase 6
/review-fix not availableLog, skip to Phase 7

Integration Points

  • Ticket system: Jira MCP, GitHub Issues, Linear, or manual input
  • Database tooling: Supabase MCP, Prisma, Drizzle, or raw SQL — auto-detected from project setup
  • GitHub CLI: gh pr create for PRs, gh pr list for past-ticket context
  • Spec/backlog files: Searched in configurable locations (see Prerequisites)
  • CLAUDE.md: Per-file-type rule cards extracted and injected into all agents
  • Design system: Theme config, global styles, and design docs read by Agent 4 (paths auto-detected from project)
  • Companion skills: /refactor and /review-fix delegated to in Phases 5-6 (gracefully skipped if unavailable)

Tips

  1. plan-only=true for complex features — review before committing to implementation
  2. Provide a ticket reference when possible — acceptance criteria drive better research and validation
  3. Override with type= to specify the feature type directly — ensures correct agent routing
  4. Check .develop-team/state.json if interrupted — resumable from last completed phase
  5. skip-review=true for quick iterations — run /refactor and /review-fix manually later
  6. skip-tests=true for prototypes — skip per-phase test generation
  7. skip-pr=true when not ready — create PR manually from synthesis report
  8. skip-migrations=true for code-only changes
  9. Zero checkpoints — fully autonomous, pauses only on genuine blockers

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Develop Team AI skill do?

This skill should be used when the user asks to "develop a feature", "implement a ticket", "build PROJ-123", "run the development pipeline", "develop this ticket end to end", or wants fully autonomous feature implementation with parallel research agents, planning, phased implementation, review, and PR creation. Zero checkpoints; pauses only on blockers.

Why use Develop Team on TypingMind?

Because you install it once and use it with any model. Develop Team is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Develop Team in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/EricTechPro/startup-claude-skills/tree/main/skills/develop-team. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Develop Team?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Develop Team?

As many as you like. As long as a model supports skills, you can use Develop Team with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Develop Team AI skill free?

Yes. It is published on GitHub by EricTechPro under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇