Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: create-plan description: Create a concise plan. Use when a user explicitly asks for a plan related to a coding task. metadata: short-description: Create a plan
Create Plan
Goal
Turn a user prompt into a single, actionable plan delivered in the final assistant message.
Minimal workflow
Throughout the entire workflow, operate in read-only mode. Do not write or update files.
-
Scan context quickly
- Read
README.mdand any obvious docs (docs/,CONTRIBUTING.md,ARCHITECTURE.md). - Skim relevant files (the ones most likely touched).
- Identify constraints (language, frameworks, CI/test commands, deployment shape).
- Read
-
Ask follow-ups only if blocking
- Ask at most 1–2 questions.
- Only ask if you cannot responsibly plan without the answer; prefer multiple-choice.
- If unsure but not blocked, make a reasonable assumption and proceed.
-
Create a plan using the template below
- Start with 1 short paragraph describing the intent and approach.
- Clearly call out what is in scope and what is not in scope in short.
- Then provide a small checklist of action items (default 6–10 items).
- Each checklist item should be a concrete action and, when helpful, mention files/commands.
- Make items atomic and ordered: discovery → changes → tests → rollout.
- Verb-first: "Add…", "Refactor…", "Verify…", "Ship…".
- Include at least one item for tests/validation and one for edge cases/risk when applicable.
- If there are unknowns, include a tiny Open questions section (max 3).
-
Do not preface the plan with meta explanations; output only the plan as per template
Plan template (follow exactly)
# Plan
<1–3 sentences: what we're doing, why, and the high-level approach.>
## Scope
- In:
- Out:
## Action items
[ ] <Step 1>
[ ] <Step 2>
[ ] <Step 3>
[ ] <Step 4>
[ ] <Step 5>
[ ] <Step 6>
## Open questions
- <Question 1>
- <Question 2>
- <Question 3>
Checklist item guidance
Good checklist items:
- Point to likely files/modules: src/..., app/..., services/...
- Name concrete validation: "Run npm test", "Add unit tests for X"
- Include safe rollout when relevant: feature flag, migration plan, rollback note
Avoid:
- Vague steps ("handle backend", "do auth")
- Too many micro-steps
- Writing code snippets (keep the plan implementation-agnostic)
More by davila7
View allTrack ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax. Use when working with .md files in Obsidian, or when the user mentions wikilinks, callouts, frontmatter, tags, embeds, or Obsidian notes.
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.
