writing-plans

Included with Lifetime

$97 forever

Use after a spec is approved - distills plan.md into context.md and a rolling markdown backlog

Writing & Docs

What this skill does


<skill_overview>
The approved spec says what must be true. `context.md` and `tasks.md` say what to do next and what was learned.
</skill_overview>

<rigidity_level>
MEDIUM FREEDOM - Verify the codebase against the spec, then write concrete task docs with no placeholders or fake certainty.
</rigidity_level>

<quick_reference>
| Step | Action | Rule |
|------|--------|------|
| 1 | Read `plan.md` | Do not restate it vaguely |
| 2 | Verify codebase reality | Prefer investigator evidence over assumptions |
| 3 | Research the task | Collect 3+ best-practice sources for the specific slice |
| 4 | Write `context.md` | Capture files, decisions, discoveries, resume notes |
| 5 | Write `tasks.md` | Use `Now`, `Next`, `Later`, `Blocked`, `Done` |
| 6 | Keep backlog lean | Only 1-2 active items in `Now` |

**Forbidden:** placeholders like `[details omitted]` or giant speculative task trees.
</quick_reference>

<when_to_use>
- Spec approved, implementation not started
- Existing task docs are vague or stale
- Need a better handoff/resume surface for a large task
</when_to_use>

<the_process>
## 1. Identify the task directory

Work in a local `plans/active/<slug>/`.
Read `plan.md` first.

## 2. Verify the codebase

Use repo inspection or `codebase-investigator` to confirm:
- real file paths
- existing modules and constraints
- likely implementation seams

Write down mismatches instead of ignoring them.

## 3. Research the specific task or feature

Before finalizing the next task slices, collect at least 3 current internet sources about:
- implementation best practices
- library or framework guidance
- common pitfalls for the specific task

Use a real web-search tool call or the `internet-researcher` agent.
Do not fill this section from memory.

Record the useful sources in `context.md`.

## 4. Populate `context.md`

Capture:
- key files
- important decisions
- discoveries from verification
- open questions
- explicit resume notes

## 5. Distill the rolling backlog

Write `tasks.md` so each item is small and concrete.

Use:
- `Now` for immediate work only
- `Next` for near-term follow-ups
- `Later` for deferred work
- `Blocked` with a reason
- `Done` for completed items

## 6. Show the real docs

Present the actual doc contents, not a summary that says “see above.”
</the_process>

<examples>
<example>
<scenario>Developer copies the spec into tasks.md verbatim</scenario>

<why_it_fails>
- No execution guidance is added
- The backlog becomes a second, worse spec
</why_it_fails>

<correction>
Keep the spec in `plan.md`; write only actionable slices in `tasks.md`.
</correction>
</example>

<example>
<scenario>Developer writes tasks against guessed file paths</scenario>

<why_it_fails>
- The first implementation step is already wrong
- The task docs lose credibility immediately
</why_it_fails>

<correction>
Verify the codebase first, then write definitive file references into `context.md`.
</correction>
</example>
</examples>

<integration>
Calls:
- `brainstorming`
- `executing-plans`
- `managing-task-docs`
</integration>

Files: 1

Size: 3.1 KB

Complexity: 5/100

Category: Writing & Docs

Source: https://github.com/withzombies/hyperpowers/tree/main/skills/writing-plans

Related in Writing & Docs

jax-development

Included

Use this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.

Writing & Docsscripts

nature-article-writer

Included

Drafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.

Writing & Docsscripts

deckrd

Included

Document-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.

Writing & Docsscripts

clinical-decision-support

Included

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

Writing & Docsscripts

handling-sf-data

Included

Salesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).

Writing & Docsscripts

accelint-ac-to-playwright

Included

Convert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.

Writing & Docsscripts