Skip to content
cccskills
FreePublished on GitHub

writing-plans

Turn specifications into detailed implementation plans before coding. Break work into testable tasks with exact file paths, code, test commands, expected results, and interfaces so another developer or agent can carry out the work.

OriginalShow the original description

Use when you have a spec or requirements for a multi-step task, before touching code

See how to install

Good for

  • Planning a feature from written requirements
  • Preparing implementation instructions for another developer
  • Defining tests before writing code
  • Checking a plan for gaps and inconsistent interfaces

Files included (2)

  • SKILL.md6.9 KB
  • plan-document-reviewer-prompt.md1.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Writing Plans

Overview

Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.

Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.

Announce at start: "I'm using the writing-plans skill to create the implementation plan."

Context: If working in an isolated worktree, it should have been created via the superpowers:using-git-worktrees skill at execution time.

Save plans to: docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md

  • (User preferences for plan location override this default)

Scope Check

If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.

File Structure

Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.

  • Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
  • You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
  • Files that change together should live together. Split by responsibility, not by technical layer.
  • In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.

This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.

Task Right-Sizing

A task is the smallest unit that carries its own test cycle and is worth a fresh reviewer's gate. When drawing task boundaries: fold setup, configuration, scaffolding, and documentation steps into the task whose deliverable needs them; split only where a reviewer could meaningfully reject one task while approving its neighbor. Each task ends with an independently testable deliverable.

Bite-Sized Task Granularity

Each step is one action (2-5 minutes):

  • "Write the failing test" - step
  • "Run it to make sure it fails" - step
  • "Implement the minimal code to make the test pass" - step
  • "Run the tests and make sure they pass" - step
  • "Commit" - step

Plan Document Header

Every plan MUST start with this header:

# [Feature Name] Implementation Plan

> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.

**Goal:** [One sentence describing what this builds]

**Architecture:** [2-3 sentences about approach]

**Tech Stack:** [Key technologies/libraries]

**Spec:** [path to the spec/design doc this plan implements — the plan
argues from the spec, so the spec travels with it; executors read both]

## Global Constraints

[The spec's project-wide requirements — version floors, dependency limits,
naming and copy rules, platform requirements — one line each, with exact
values copied verbatim from the spec. Every task's requirements implicitly
include this section.]

---

Task Structure

### Task N: [Component Name]

**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`

**Interfaces:**
- Consumes: [what this task uses from earlier tasks — exact signatures]
- Produces: [what later tasks rely on — exact function names, parameter
  and return types. A task's implementer sees only their own task; this
  block is how they learn the names and types neighboring tasks use.]

- [ ] **Step 1: Write the failing test**

```python
def test_specific_behavior():
    result = function(input)
    assert result == expected
```

- [ ] **Step 2: Run test to verify it fails**

Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"

- [ ] **Step 3: Write minimal implementation**

```python
def function(input):
    return expected
```

- [ ] **Step 4: Run test to verify it passes**

Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS

- [ ] **Step 5: Commit**

```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```

No Placeholders

Every step must contain the actual content an engineer needs. These are plan failures — never write them:

  • "TBD", "TODO", "implement later", "fill in details"
  • "Add appropriate error handling" / "add validation" / "handle edge cases"
  • "Write tests for the above" (without actual test code)
  • "Similar to Task N" (repeat the code — the engineer may be reading tasks out of order)
  • Steps that describe what to do without showing how (code blocks required for code steps)
  • References to types, functions, or methods not defined in any task

Self-Review

After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.

1. Spec coverage: Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.

2. Placeholder scan: Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.

3. Type consistency: Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called clearLayers() in Task 3 but clearFullLayers() in Task 7 is a bug.

If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.

Execution Handoff

After saving the plan, offer execution choice:

"Plan complete and saved to docs/superpowers/plans/<filename>.md. Two execution options:

1. Subagent-Driven (recommended) - I dispatch a fresh subagent per task, review between tasks, fast iteration

2. Inline Execution - Execute tasks in this session using executing-plans, batch execution with checkpoints

Which approach?"

If Subagent-Driven chosen:

  • REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development
  • Fresh subagent per task + two-stage review

If Inline Execution chosen:

  • REQUIRED SUB-SKILL: Use superpowers:executing-plans
  • Batch execution with checkpoints for review

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

brainstorming

FreeSummary

Turn development ideas into clear designs through guided discussion. The skill clarifies goals, requirements, and constraints, then adapts the process to a feasibility investigation, a small existing-code change, or a larger architectural design.

  • Clarifying requirements before adding a feature
  • Exploring whether an idea is feasible
  • Comparing designs for a new project
spacering-net/codeg4.1KUpdated Oct 21, 2026

Find academic papers, retrieve publication details, and build BibTeX reference files for scholarly writing. Check identifiers, missing information, duplicate entries, and mismatches between manuscript citations and the bibliography, with tools for formatting and validation.

  • Finding papers for a manuscript or thesis
  • Converting paper identifiers into BibTeX entries
  • Cleaning duplicate or incomplete references
spacering-net/codeg4.1KUpdated Oct 21, 2026

Assign independent bugs or test failures to separate agents that work at the same time. Define each agent’s scope and expected report, then check for conflicting changes and run the full test suite before integrating fixes.

  • Investigating test failures with unrelated causes
  • Fixing independent problems in separate subsystems
  • Defining focused tasks for multiple agents
spacering-net/codeg4.1KUpdated Oct 21, 2026

executing-plans

FreeSummary

Carry out a written implementation plan in a separate session, reviewing it before starting and tracking each task through verification. The workflow pauses for blockers and hands completed work to a development branch finishing process.

  • Executing a written implementation plan
  • Tracking task progress and verification
  • Reviewing gaps before implementation
spacering-net/codeg4.1KUpdated Oct 21, 2026

Plan experiments before collecting data by choosing how to assign samples, combine conditions, and order runs. Generate reproducible allocation schedules and experimental layouts while checking for design flaws that could make results difficult to interpret.

  • Assigning subjects or samples to comparison groups
  • Screening many factors to identify promising ones
  • Planning around batch, day, or plate-position differences
spacering-net/codeg4.1KUpdated Oct 21, 2026

Explore scientific data files to understand their structure, statistical patterns, and quality. References cover over 200 formats, with workflows for producing Markdown reports that summarize findings and recommend preprocessing, visualizations, and further analysis.

  • Checking missing values and outliers in experimental tables
  • Examining sequence lengths and quality scores in FASTQ files
  • Inspecting microscopy image dimensions and metadata
spacering-net/codeg4.1KUpdated Oct 21, 2026

See all skills by spacering-net

Report a problem with this skill