spec-kitty-tasks-outline
🔗 Workflow Provenance
Source: This skill augments the baseline workflow located at
./workflows/spec-kitty.tasks-outline.md. It acts as an intelligent wrapper that is continuously improved with each execution.
/spec-kitty.tasks-outline - Create Task Breakdown Document
Version: 0.12.0+
Purpose
Create tasks.md — the task breakdown document that defines work packages,
subtask lists, dependency descriptions, and sizing estimates. This step
produces the outline only; individual WP prompt files are generated in
the next step.
⚠️ CRITICAL: THIS IS THE MOST IMPORTANT PLANNING WORK
You are creating the blueprint for implementation. The quality of work packages determines:
- How easily agents can implement the feature
- How parallelizable the work is
- How reviewable the code will be
- Whether the feature succeeds or fails
QUALITY OVER SPEED: Take your time to understand the full scope deeply, break work into clear pieces, and write detailed guidance.
📍 WORKING DIRECTORY: Stay in the project root checkout
IMPORTANT: This step works in the project root checkout. NO worktrees created.
Do NOT cd anywhere. Stay in the project root checkout root.
In repos with multiple features, always pass --feature <slug> to every spec-kitty command.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Context Resolution
Before proceeding, resolve canonical command context:
spec-kitty agent context resolve --action tasks_outline --json
Treat that JSON as canonical for feature slug, feature directory, and target branch. Do not probe git branch state manually inside the prompt.
Steps
1. Setup
Run the exact check_prerequisites command returned by the resolver. Capture
feature_dir plus available_docs. All paths must be absolute.
CRITICAL: The command returns JSON with feature_dir as an ABSOLUTE path. YOU MUST USE THIS PATH for ALL subsequent file operations.
2. Load Design Documents
Read from feature_dir (only those present):
- Required: plan.md (tech architecture, stack), spec.md (user stories & priorities)
- Optional: data-model.md (entities), contracts/ (API schemas), research.md (decisions), quickstart.md (validation scenarios)
Scale your effort to the feature: simple UI tweaks deserve lighter coverage, multi-system releases require deeper decomposition.
3. Derive Fine-Grained Subtasks
Create complete list of subtasks with IDs T001, T002, etc.:
- Parse plan/spec to enumerate concrete implementation steps, tests (only if explicitly requested), migrations, and operational work.
- Capture prerequisites, dependencies, and parallelizability markers (
[P]means safe to parallelize per file/concern). - Assign IDs sequentially in execution order.
- Ideal granularity: One clear action (e.g., "Create user model", "Add login endpoint")
4. Roll Subtasks into Work Packages
Group subtasks into work packages (IDs WP01, WP02, ...):
TARGET SIZE: 3-7 subtasks per WP (200-500 line prompts) MAXIMUM: 10 subtasks per WP (700 line prompts) If more than 10 subtasks needed: Create additional WPs, don't pack them in
GROUPING PRINCIPLES:
- Each WP should be independently implementable
- Root in a single user story or cohesive subsystem
- Ensure every subtask appears in exactly one work package
- Name with succinct goal (e.g., "User Story 1 – Real-time chat happy path")
- Record metadata: priority, success criteria, risks, dependencies, included subtasks, and requirement references
- Every WP must include a
Requirement Refsline listing IDs fromspec.md(FR/NFR/C)
5. Write tasks.md
Write to feature_dir/tasks.md following the tasks template structure below (do NOT write instructions to read a template file from .kittify/):
- Populate Work Package sections (setup, foundational, per-story, polish) with
WPxxentries - Under each work package include:
- Summary (goal, priority, independent test)
- Requirement references (
Requirement Refs: FR-001, NFR-001, C-001) - Included subtasks (checkbox list referencing
Txxx) - Implementation sketch (high-level sequence)
- Parallel opportunities, dependencies, and risks
- Estimated prompt size (e.g., "~400 lines")
- Add a
Requirements Coverage Summarysection mapping every requirement ID inspec.mdto one or more WPs - Preserve the checklist style so implementers can mark progress
DO NOT generate WP prompt files in this step. That happens in the next step.
Output
After completing this step:
feature_dir/tasks.mdexists with full work package definitions- Each WP has clear subtask lists, dependencies, and sizing estimates
- No WP prompt files have been created yet
Next step: spec-kitty next --agent <name> will advance to work package generation.
Work Package Sizing Guidelines
Target: 3-7 subtasks per WP → 200-500 line prompts Maximum: 10 subtasks → ~700 line prompts No arbitrary limit on WP count — let complexity dictate
Split if ANY of these are true:
- More than 10 subtasks
- Prompt would exceed 700 lines
- Multiple independent concerns mixed together
- Different phases or priorities mixed
Merge if ALL of these are true:
- Each WP has <3 subtasks
- Combined would be <7 subtasks
- Both address the same concern/component
- No natural parallelization opportunity
Dependency Detection
Analyze tasks.md for dependency relationships:
- Explicit phrases: "Depends on WP##", "Dependencies: WP##"
- Phase grouping: Phase 2 WPs typically depend on Phase 1
- Default to empty if unclear
Document dependencies clearly in each WP's section.
Context for work-package planning: $ARGUMENTS
More from richfrem/agent-plugins-skills
markdown-to-msword-converter
Converts Markdown files to one MS Word document per file using plugin-local scripts. V2 includes L5 Delegated Constraint Verification for strict binary artifact linting.
52excel-to-csv
>
32zip-bundling
Create technical ZIP bundles of code, design, and documentation for external review or context sharing. Use when you need to package multiple project files into a portable `.zip` archive instead of a single Markdown file.
29learning-loop
(Industry standard: Loop Agent / Single Agent) Primary Use Case: Self-contained research, content generation, and exploration where no inner delegation is required. Self-directed research and knowledge capture loop. Use when: starting a session (Orientation), performing research (Synthesis), or closing a session (Seal, Persist, Retrospective). Ensures knowledge survives across isolated agent sessions.
26ollama-launch
Start and verify the local Ollama LLM server. Use when Ollama is needed for RLM distillation, seal snapshots, embeddings, or any local LLM inference — and it's not already running. Checks if Ollama is running, starts it if not, and verifies the health endpoint.
26spec-kitty-checklist
A standard Spec-Kitty workflow routine.
26