Implement Issue

Community

aaddrick

implement-issue

Use when given a GitHub issue number and base branch to implement end-to-end

Overview

Publisher	aaddrick
Repository	`claude-pipeline`
Skill name	`implement-issue`
Stars	130
Forks	17
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by aaddrick on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/aaddrick/claude-pipeline/tree/main/.claude/skills/implement-issue
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.

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/aaddrick/claude-pipeline.git /tmp/claude-pipeline
mkdir -p .claude/skills
cp -r /tmp/claude-pipeline/.claude/skills/implement-issue .claude/skills/implement-issue

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Implement Issue 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 Implement Issue 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 Implement Issue 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.

Implement Issue

End-to-end issue implementation via orchestrator script.

Announce at start: "Using implement-issue to run orchestrator for #$ISSUE against $BRANCH"

Arguments:

$1 — GitHub issue number (required)
$2 — Base branch name (required)

Invocation

Immediately launch the orchestrator:

bash
.claude/scripts/implement-issue-orchestrator.sh \
  --issue $ISSUE_NUMBER \
  --branch $BASE_BRANCH

Or with explicit agent override:

bash
.claude/scripts/implement-issue-orchestrator.sh \
  --issue $ISSUE_NUMBER \
  --branch $BASE_BRANCH \
  --agent bulletproof-frontend-developer

Monitoring

Each run creates its own status.json inside the log directory:

bash
# Find the latest run's status file
jq . logs/implement-issue/issue-${ISSUE_NUMBER}-*/status.json

Watch live:

bash
# Replace with your actual log dir path (shown at startup)
watch -n 5 'jq -c "{state,stage:.current_stage,task:.current_task,quality:.quality_iterations}" logs/implement-issue/issue-123-20260221-153045-12345/status.json'

Stages

Stage	Agent	Description
setup	default	fetch, worktree, research, evaluate, plan
implement	per-task	execute each task from plan
task-review	spec-reviewer	verify task achieved goal
fix	per-task	address review findings (uses task's agent)
simplify	code-simplifier	clean up code
test	php-test-validator	run test suite
review	code-reviewer	internal code review
docs	phpdoc-writer	add PHPDoc blocks
pr	default	create/update PR
spec-review	spec-reviewer	verify PR achieves issue goals
code-review	code-reviewer	final code quality check
tech-docs	technical-doc-writer	assess/write/update docs in docs/{domain}/
complete	default	post summary

Available Implementation Agents

The plan stage selects the best agent per task from:

Agent	Use For
laravel-backend-developer	PHP/Laravel: controllers, models, services, middleware, migrations, API, PHPUnit
bulletproof-frontend-developer	CSS, responsive design, Blade templates, frontend code
bash-script-craftsman	Shell scripts, portability, BATS tests
technical-doc-writer	Architecture docs, design docs, data flows, API contracts in docs/{domain}/

Schemas

Located in .claude/scripts/schemas/implement-issue-*.json

Logging

Logs written to logs/implement-issue/issue-N-timestamp/:

orchestrator.log — main log
stages/ — per-stage Claude output
context/ — parsed outputs (tasks.json, etc.)
status.json — real-time status (primary location, no root-level status.json)

Exit Codes

Code	Meaning
0	Success, PR created and approved
1	Error during a stage
2	Max iterations exceeded
3	Configuration/argument error

CLI Session Isolation

All claude -p invocations in orchestrator scripts must use --no-resume to prevent session context contamination. Without it, the CLI may resume a cached session and the model will return "already processed" instead of following the schema prompt — causing "No structured output" failures.

Exception: Explicit --resume $SESSION_ID after rate limit recovery is intentional and correct.

Integration

Called by handle-issues via batch-orchestrator.sh.

Frequently asked questions

What does the Implement Issue AI skill do?

Use when given a GitHub issue number and base branch to implement end-to-end

Why use Implement Issue on TypingMind?

Because you install it once and use it with any model. Implement Issue 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 Implement Issue in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aaddrick/claude-pipeline/tree/main/.claude/skills/implement-issue. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Implement Issue?

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 Implement Issue?

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

Is the Implement Issue AI skill free?

Yes. It is published on GitHub by aaddrick 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

Plan Canvas

affaan-m

CommunityPopular

Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or…

Improve Codebase Architecture

mattpocock

CommunityPopular

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Grilling

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

Teach

Teach the user a new skill or concept, within this workspace.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Implement Issue

Invocation

Monitoring

Stages

Available Implementation Agents

Schemas

Logging

Exit Codes

CLI Session Isolation

Integration

Frequently asked questions

Related AI Skills

Set up your own AI workspace now