agentsclimarketplace

Task

Skill yokeloop/yoke/deprecated/task

Claude Code plugin and marketplace of skills & commands for the full dev loop: /task → /plan → /do → /review → /gca → /gp → /pr. Plus /prd, /issues, /explore, /grill, /bootstrap, /handoff and more.

Install
npx -y skills add yokeloop/yoke --skill task

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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Drafts a task file for AI implementation. Triggered when the user writes "create a task", "task from ticket", "draft a task", "prepare an implementation prompt", or passes a ticket URL / feature description.

SKILL.md

7.8 KB, as published. Nobody here has run it

Draft a task for AI implementation

Orchestrate sub-agents and communicate with the user.

Delegate codebase investigation through the Agent tool:

  • Investigation → agents/task-investigator.md

Formulate the task; implementation belongs to other skills.


Input

$ARGUMENTS contains one or both of:

  • Ticket URL — GitHub Issues, YouTrack, Jira, etc.
  • Task text — description, code snippets, links

Phases

Phase 1 — Parse

1. Fetch the ticket:

  • GitHub Issues → gh issue view <url>
  • Other trackers → take the content from the user's text; use the URL only for the slug

2. Extract materials from the input: Collect a separate list of:

  • links (Figma, docs, API)
  • paths to files and screenshots
  • pasted code snippets
  • external resources

Copy this list verbatim into the Materials section.

3. Build the task slug — identifier + English kebab-case description:

  • 86-black-jack-page — from GitHub issue #86
  • R2-50-user-id-to-db — from YouTrack R2-50
  • fix-navbar-overflow — no URL, text only

Take the ID from the URL plus 2–4 descriptive words. With no URL, use the description only.

4. Extract TICKET_ID from the slug (per ${CLAUDE_PLUGIN_ROOT}/skills/gca/reference/commit-convention.md).

Transition: slug and TICKET_ID determined, materials saved → Phase 2.


Phase 2 — Investigate

Launch task-investigator through the Agent tool. The agent definition lives in agents/task-investigator.md.

Prompt to the agent:

Investigate the codebase area for this task: [paste the ticket essence].

Find and document:
1. Entry points with file:line
2. Patterns to reuse (1-2 similar implementations)
3. Tests covering the area, or note their absence
4. Integration risks and fragile dependencies
5. Reusable utilities, components, or patterns

Stop criteria — Investigate is done when:

  • Entry points are identified with line numbers
  • Patterns to reuse are found with example files
  • Tests for the touched area are listed, or confirm their absence
  • Risk zones are identified

If any item stays open, re-dispatch task-investigator with narrower scope.

Transition: all four criteria closed → Phase 3.


Phase 3 — Synthesize

Apply the 5-dimension checklist to Phase 2 findings. For each: one sentence of reasoning, then the formulation.

  1. Intent Clarity. Two developers should read the Task and do the same thing. Use one concrete verb per Task — not "improve" or "fix".
  2. Scope Boundaries. State what is in scope and what is out. Each Constraint maps to a concrete risk from Investigate: a fragile file, similar code that must stay, a dependency surface.
  3. Context Anchoring. Cite paths and line numbers — src/auth/middleware.ts:validateToken():89, not "the auth module". Context has 4 subsections: Area architecture, Files to change, Patterns to reuse, Tests.
  4. Acceptance Criteria. Write each Verification bullet as a command with expected result OR an observable behavior. Pull edge cases from Investigate findings.
  5. Reuse Opportunities. For each requirement, find a partial existing solution. Record under Patterns to reuse with paths.

Complexity: trivial (1 file, ≤5 lines) / simple (1-2 files, clear scope) / medium (3-7 files, possible regressions) / complex (architecture, multiple layers, no tests, public API).

If the task touches UI components, styles, or frontend work (React, Vue, Svelte, CSS, Tailwind, animations, layouts, pages): read reference/frontend-guide.md and apply its checklists to the Requirements, Constraints, and Verification dimensions.

For deeper Bad/Good examples and anti-patterns, see reference/synthesize-guide.md — supplementary.

Question validation:

Re-read $ARGUMENTS. Keep only questions the prompt leaves open. Fold the user's decisions into Requirements and Constraints as facts.

Interactive clarifications:

Draft 3–7 clarifying questions whose answers change requirements, scope, or architecture. Ask the user via AskUserQuestion in batches of 1–4 questions.

For each question:

  • 2–4 answer options with explanations
  • Recommended option first, labeled (Recommended)
  • The user may pick "Other" for free-form input

After each batch, revise Requirements, Constraints, and Context. Fold the answers into the section wording.

Repeat until the user answers every question.

Transition: 5 dimensions applied, questions asked and answers folded in → Phase 4.


Phase 4 — Write

1. mkdir -p .yoke/ai/<task-slug>

2. Write .yoke/ai/<task-slug>/<task-slug>-task.md:

# <Task title>

**Slug:** <task-slug>
**Ticket:** <URL or "—">
**Complexity:** <trivial | simple | medium | complex>
**Type:** <frontend | general>

## Task

<One sentence — what to do.>

## Context

### Area architecture
<Data flow, entry points, abstraction layers>

### Files to change
<Paths + lines — entry points for implementation>

### Patterns to reuse
<Similar implementations with paths — what to reuse>

### Tests
<Existing coverage, what to cover next>

## Requirements

1. <Concrete, verifiable requirement>
2. ...

## Constraints

- <What NOT to change>
- <Which approaches to avoid>
- <What not to break>

## Verification

- `<command>` → <expected result>
- <expected behavior>
- <edge cases>

## Materials

- [Description](url)
- `path/to/file`

3. Self-check the prose — re-read the file. Edit inline if any sentence violates:

  • Active voice — "the agent reads the file"
  • Positive form — "Add tests" (not "Don't forget tests")
  • Concrete language — files, lines, function names
  • No needless words
  • Imperative mood

4. Auto-commit the artifact.

Check: is .yoke/ in .gitignore? If yes — tell the user and skip the commit.

Otherwise commit per the convention in ${CLAUDE_PLUGIN_ROOT}/skills/gca/reference/commit-convention.md:

git add .yoke/ai/<task-slug>/<task-slug>-task.md
git commit -m "TICKET docs(SLUG): add task definition"

Format: TICKET docs(SLUG): add task definition (NO colon after ticket). Example: #86 docs(86-black-jack-page): add task definition. Commit only the task artifact, no other files.

Transition → Phase 5.


Phase 5 — Complete

Report the file path and task slug, then run the finishing loop.

Send a notification: bash ${CLAUDE_PLUGIN_ROOT}/lib/notify.sh --type STAGE_COMPLETE --skill task --phase Complete --slug "$TASK_SLUG" --title "Task ready" --body ".yoke/ai/$TASK_SLUG/$TASK_SLUG-task.md"

Offer next step:

Offer 3 options through AskUserQuestion:

  1. Run /yoke:plan (Recommended) — auto-handoff to planning
  2. Review via revdiff — interactive review of the task file
  3. Finish — exit

Handle the choice (one-shot, no loop):

  • Run /yoke:plan: call the Skill tool with /yoke:plan and the argument .yoke/ai/<task-slug>/<task-slug>-task.md. Exit.
  • Review via revdiff: call the Skill tool with /revdiff and the argument --only .yoke/ai/<task-slug>/<task-slug>-task.md. If the return is non-empty, apply the annotations to the task file and overwrite. Then exit. (For another pass, the user invokes /revdiff manually.) If the plugin is missing — print Install the revdiff plugin: followed by /plugin marketplace add umputun/revdiff and /plugin install revdiff@umputun-revdiff, then exit.
  • Finish: report the file path. Exit.

Rules

  • Language: match the ticket/input language, or follow the project-level definition in CLAUDE.md / AGENTS.md.
  • task-slug — English kebab-case
  • One task — one file, no decomposition
  • Write in active voice. Omit needless words. Name files and lines instead of abstractions.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.