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Agent Orchestration
Skill

/task-planning

Structured task planning workflow with user feedback loops. Use when the user explicitly requests planning (e.g., "make a plan", "plan first", "create a plan"). Covers creating plans with actionable steps, iterating based on feedback, saving confirmed plans, and executing

BOOST
From plugin
freeact
1303 skills
Install
$ npx -y skills add gradion-ai/freeact --skill task-planning --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/task-planning

Context preview

The summary Claude sees to decide when to auto-load this skill.

Structured task planning workflow with user feedback loops. Use when the user explicitly requests planning (e.g., "make a plan", "plan first", "create a plan"). Covers creating plans with actionable steps, iterating based on feedback, saving confirmed plans, and executing

SKILL.md

task-planning.SKILL.md
name: task-planning
description: Structured task planning workflow with user feedback loops. Use when the user explicitly requests planning (e.g., "make a plan", "plan first", "create a plan"). Covers creating plans with actionable steps, iterating based on feedback, saving confirmed plans, and executing step-by-step with progress tracking.

Task Planning

Structured workflow for planning and executing tasks when explicitly requested by the user.

Planning Phase

1. Create Initial Plan

Draft a plan with clear, actionable steps using markdown checklist format:

- [ ] Step 1: Description
- [ ] Step 2: Description
- [ ] Step 3: Description

2. Request Feedback

Present the plan to the user and ask for feedback. Do not proceed until feedback is received.

3. Iterate Until Confirmed

Revise the plan based on user feedback. Continue the proposal-feedback loop until the user confirms.

4. Save Confirmed Plan

Write the confirmed plan to `{plans_rel_dir}/<task-name>.md` where:

  • `<task-name>` is a descriptive kebab-case name
  • Example: `{plans_rel_dir}/add-user-authentication.md`
  • The `{plans_rel_dir}/` directory already exists

Execution Phase

5. Execute Step-by-Step

Work through the plan sequentially:

  • First unchecked item is the current task
  • After completing each step, mark with checkmark: `- [x] Step description`
  • Update the plan file to reflect progress

6. Revise as Needed

If execution reveals the need for plan adjustments:

  • Update the plan file with revised steps
  • Inform the user of significant changes

7. Request Feedback During Execution

If encountering uncertainty or needing user input during execution, ask for feedback before proceeding.

Plan File Format

# <Task Title>

## Steps

- [x] Completed step
- [ ] Pending step
- [ ] Another pending step

## Notes

Optional section for context, decisions made, or issues encountered.
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Ships withfreeact

General-purpose AI agent that acts via code actions through a unified execution interface.

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130
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10
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Maintained
Maintenance
Python
Language
Apache-2.0
License
3mo ago
Last commit
1y ago
Created
19h ago
Added

Repo: gradion-ai/freeact

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