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Work

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oliver-kriska
work

Execute Elixir/Phoenix plan tasks with progress tracking. Use after /phx:plan to implement features with mix compile and mix test verification after each step, or --continue to resume interrupted work.

Overview

Publisheroliver-kriska
Repositoryclaude-elixir-phoenix
Skill namework
Stars
555
Forks
40
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

    Published by oliver-kriska on GitHub. Read the source before you install it.

Installation

Install the Work 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.
  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/oliver-kriska/claude-elixir-phoenix.git /tmp/claude-elixir-phoenix
mkdir -p .claude/skills
cp -r /tmp/claude-elixir-phoenix/plugins/elixir-phoenix/skills/work .claude/skills/work
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Work 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 Work 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 Work 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.

Work

Execute tasks from a plan file with checkpoint tracking and verification.

Usage

/phx:work .claude/plans/user-auth/plan.md
/phx:work .claude/plans/user-auth/plan.md --from P2-T3
/phx:work --skip-blockers
/phx:work  # Resumes most recent plan

Arguments

  • <plan-file> -- Path to plan file (optional, auto-detects recent)
  • --from <task-id> -- Resume from specific task (e.g., P2-T3)
  • --skip-blockers -- Continue past blocked tasks
  • --continue -- Resume IN_PROGRESS plan from checkboxes

Iron Laws (NON-NEGOTIABLE)

  1. NEVER auto-proceed to /phx:review or any next workflow phase -- always ask the user what to do next
  2. AUTO-CONTINUE between plan phases -- when Phase N completes, immediately start Phase N+1. Do NOT stop or ask for permission between phases. Only stop at BLOCKERS or when ALL phases are done.
  3. Plan checkboxes ARE the state -- [x] = done, [ ] = pending. No separate JSON state files. Resume by reading the plan.
  4. Verify after EVERY task -- never skip verification
  5. Max 3 retries then BLOCKER -- don't keep retrying forever
  6. Stage specific files -- never use git add -A or git add .
  7. Read scratchpad BEFORE implementing -- scratchpad has dead-ends and decisions that prevent rework. Step 2 is not optional.
  8. Clarify ambiguous tasks -- ask the user rather than guessing when a plan task's intent is unclear

Step 1: Research Decision

Ask the user for plans with >3 tasks:

This plan has {count} remaining tasks across {count} phases.

  1. Start working -- Begin immediately (familiar patterns)
  2. Quick research -- Read source files first (~10 min)
  3. Extensive research -- Web search + docs (~30 min)

Skip for plans with 3 or fewer simple tasks -- just start.

Split warning: Plans with >10 tasks risk 2-3 context compactions. Suggest splitting via /phx:plan if not already.

Step 2: Check Context (MANDATORY)

Read scratchpad and compound docs before writing any code — skipping this causes rework. Read .claude/plans/{slug}/scratchpad.md (short, critical context) for dead-ends and decisions, then Grep .claude/solutions/ for solved patterns. Apply findings: skip dead-ends, follow decisions, reuse patterns. Ask the user when a task's intent is ambiguous — never guess, corrections are expensive.

Step 3: Load, Create Task List, and Resume

Read plan file, count [x] (completed) vs [ ] (remaining). Find first unchecked task by [Pn-Tm] ID.

Create Claude Code tasks from ALL unchecked plan items using TaskCreate. This gives real-time progress visibility in the UI:

For each unchecked `- [ ] [Pn-Tm] Description`:
  TaskCreate({
    subject: "[Pn-Tm] Description",
    description: "Full task details from plan",
    activeForm: "Implementing: Description"
  })

Skip already-checked items ([x]) — don't create tasks for them. Set up blockedBy dependencies between phases (Phase 2 tasks blocked by Phase 1 tasks).

With --from P2-T3: Skip to that specific task.

Stale-plan check: if the plan predates this session (file mtime), spot-check 2-3 files it references before executing — assumptions may have drifted.

See ${CLAUDE_SKILL_DIR}/references/resume-strategies.md for all resume modes.

Step 4: Execute Tasks

Execute each unchecked task (- [ ] [Pn-Tm][agent] Description):

  1. Start task: TaskUpdate({taskId, status: "in_progress"})
  2. Route by [agent] annotation (see ${CLAUDE_SKILL_DIR}/references/execution-guide.md)
  3. Implement the task
  4. Verify: mix format + mix compile --warnings-as-errors (at phase end, also run mix test <affected> — see tiers below)
  5. Complete task: Mark checkbox [x] on pass, append implementation note inline, AND TaskUpdate({taskId, status: "completed"}). Example: - [x] [P1-T3] Add user schema — citext for email, composite index on [user_id, status] This survives context compaction; the plan is re-read on resume.
  6. On failure: retry up to 3 times, then create BLOCKER and write DEAD-END to scratchpad (see error-recovery.md)

Parallel groups: Tasks under ### Parallel: header spawn as background subagents. See ${CLAUDE_SKILL_DIR}/references/execution-guide.md for spawning pattern, prompt template, and checkpoint flow.

Verification tiers (scoped to minimize redundant runs):

  • Per-task: mix compile --warnings-as-errors only (format is checked by PostToolUse hook automatically)
  • Per-phase: mix compile --warnings-as-errors + mix test <affected_files> + mix credo --strict (scope tests: mix test test/path/to_affected_test.exs — NOT full suite)
  • Per-feature (Tidewave): behavioral smoke test via project_eval (create record, fetch, verify -- see execution-guide.md)
  • Final gate: mix test (full suite — run ONCE at the end, not per-phase)

Token efficiency: Do NOT narrate each verification step. Execute tool calls directly without "Let me now run..." preamble. Only narrate when explaining a non-obvious decision or reporting a failure. When several checkboxes complete together (parallel groups, resume catch-up), batch them into ONE edit pass — never one Edit call per checkbox. The PostToolUse hook checks formatting but does NOT modify files — run mix format explicitly during verification or before committing.

Step 5: Completion

Summarize results with AskUserQuestion:

Implementation complete! {done}/{total} tasks finished. {count} files modified across {count} phases.

Options: 1. Run review (/phx:review) (Recommended), 2. Get a briefing (/phx:brief — understand what was built), 3. Commit changes (/commit), 4. Continue manually. If any task fixed a non-obvious bug, also mention /phx:compound to capture the solution.

With blockers: list them, offer Replan (/phx:plan), Review first (/phx:review), or Handle myself.

If blockers remain, auto-write HANDOFF to scratchpad:

markdown
### [HH:MM] HANDOFF: {plan name}
Status: {done}/{total} tasks. Blockers: {list}.
Next: {first unchecked task ID and description}.
Key decisions: {brief list from this session}.

Include context beyond checkboxes for fresh session resume.

NEVER auto-start /phx:review or any other phase.

Step 6: Check for Additional Plans

After completion, use Glob to find other plan files matching .claude/plans/*/plan.md. If pending plans exist, inform the user. Do NOT auto-start.

Integration

text
/phx:plan → /phx:work (YOU ARE HERE) → /phx:review → /phx:compound
                 ↑ ASK USER before each transition

References

  • ${CLAUDE_SKILL_DIR}/references/execution-guide.md -- Task routing, parallel execution, verification
  • ${CLAUDE_SKILL_DIR}/references/resume-strategies.md -- Resume modes and state persistence
  • ${CLAUDE_SKILL_DIR}/references/file-formats.md -- Plan and progress file formats
  • ${CLAUDE_SKILL_DIR}/references/error-recovery.md -- Error handling and blockers
  • ${CLAUDE_SKILL_DIR}/references/harness-patterns.md -- Critic-refiner pattern for debugging loops

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 Work AI skill do?

Execute Elixir/Phoenix plan tasks with progress tracking. Use after /phx:plan to implement features with mix compile and mix test verification after each step, or --continue to resume interrupted work.

Why use Work on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oliver-kriska/claude-elixir-phoenix/tree/main/plugins/elixir-phoenix/skills/work. 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 Work?

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 Work?

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

Is the Work AI skill free?

Yes. It is published on GitHub by oliver-kriska 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.

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