agent planning skill risk: low
Concise Coding Task Planner
Turns a user request for a coding task into a single actionable plan with atomic steps, following a workflow of scanning context, minimal interaction, and a fixed markdown template…
SKILL 1 file
SKILL.md
--- name: antigravity-awesome-skills-concise-planning description: "Use when a user asks for a plan for a coding task, to generate a clear, actionable, and atomic checklist." --- # Concise Planning ## Goal Turn a user request into a **single, actionable plan** with atomic steps. ## Workflow ### 1. Scan Context - Read `README.md`, docs, and relevant code files. - Identify constraints (language, frameworks, tests). ### 2. Minimal Interaction - Ask **at most 1–2 questions** and only if truly blocking. - Make reasonable assumptions for non-blocking unknowns. ### 3. Generate Plan Use the following structure: - **Approach**: 1-3 sentences on what and why. - **Scope**: Bullet points for "In" and "Out". - **Action Items**: A list of 6-10 atomic, ordered tasks (Verb-first). - **Validation**: At least one item for testing. ## Plan Template ```markdown # Plan <High-level approach> ## Scope - In: - Out: ## Action Items [ ] <Step 1: Discovery> [ ] <Step 2: Implementation> [ ] <Step 3: Implementation> [ ] <Step 4: Validation/Testing> [ ] <Step 5: Rollout/Commit> ## Open Questions - <Question 1 (max 3)> ``` ## Checklist Guidelines - **Atomic**: Each step should be a single logical unit of work. - **Verb-first**: "Add...", "Refactor...", "Verify...". - **Concrete**: Name specific files or modules when possible. ## When to Use This skill is applicable to execute the workflow or actions described in the overview. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
REQUIRED CONTEXT
- user request for coding task
- README.md
- docs
- relevant code files
ROLES & RULES
- Read README.md, docs, and relevant code files.
- Identify constraints (language, frameworks, tests).
- Ask at most 1–2 questions and only if truly blocking.
- Make reasonable assumptions for non-blocking unknowns.
- Use the following structure for the plan.
- Each step should be a single logical unit of work.
- Use verb-first phrasing for steps.
- Name specific files or modules when possible.
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
EXPECTED OUTPUT
- Format
- markdown
- Schema
- markdown_sections · Plan, Scope, Action Items, Open Questions
- Constraints
- use exact Plan Template structure
- 6-10 atomic verb-first action items
- at most 3 open questions
- include Scope In/Out and Validation
SUCCESS CRITERIA
- Turn a user request into a single, actionable plan with atomic steps.
- Produce 6-10 atomic, ordered, verb-first tasks.
- Include at least one validation/testing item.
- Limit open questions to at most 3.
FAILURE MODES
- May produce non-atomic steps.
- May exceed the 1-2 question limit.
CAVEATS
- Dependencies
- README.md
- docs
- relevant code files
- Missing context
- How the user request and project context (files) are supplied to the model.
- Ambiguities
- The 'When to Use' section references an 'overview' that is not present in the prompt.
- 'execute the workflow or actions described in the overview' is unclear and self-referential.
QUALITY
- OVERALL
- 0.74
- CLARITY
- 0.75
- SPECIFICITY
- 0.82
- REUSABILITY
- 0.78
- COMPLETENESS
- 0.68
IMPROVEMENT SUGGESTIONS
- Replace the vague 'When to Use' paragraph with a concise, self-contained trigger condition.
- Add an explicit 'Input' section describing the expected format of the user request and available files.
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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