plan-task-planner

plan-task-planner is a skill for Claude Code from ThiagoGuislotti/copilot-instructions. It costs 43 tokens per session (343 once invoked), scanned A, original, MIT.

A planning guide for breaking complex implementation work into ordered, testable tasks with dependencies, target files, commands, checkpoints, and risks.

In plain words
What is it for?
Use it for implementation plans, roadmaps, effort estimates, multi-step delivery, validation steps, and pull-request preparation.
Why use it?
It turns a broad engineering request into an execution sequence that another developer or agent can follow and verify.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions AGENTS.md.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/thiagoguislotti/copilot-instructions/plan-task-planner
Any agent
npx skills add ThiagoGuislotti/copilot-instructions --skill plan-task-planner
Clone the repo
git clone --depth 1 https://github.com/ThiagoGuislotti/copilot-instructions

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for plan-task-planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/thiagoguislotti/copilot-instructions/plan-task-planner.svg)](https://agentmods.dev/skills/thiagoguislotti/copilot-instructions/plan-task-planner)
Your own site
<a href="https://agentmods.dev/skills/thiagoguislotti/copilot-instructions/plan-task-planner"><img src="https://agentmods.dev/badge/skills/thiagoguislotti/copilot-instructions/plan-task-planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 343 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.00343
Opus 5 $0.00022 $0.00171
Sonnet 5 $0.00009 $0.00069
Haiku 4.5 $0.00004 $0.00034

Measured 5d ago against content hash f8ae5b36aefe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

plan-task-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/plan-task-planner/SKILL.md · 42 lines

What it actually says

Task Planner

Load context first

  1. .github/AGENTS.md
  2. .github/copilot-instructions.md
  3. .github/instructions/repository-operating-model.instructions.md

Planning instruction pack

  • .github/instructions/workflow-optimization.instructions.md
  • .github/instructions/effort-estimation-ucp.instructions.md
  • .github/instructions/pr.instructions.md (when output is PR-oriented)
  • .github/instructions/feedback-changelog.instructions.md (when release/change log impact exists)

Claude-native execution

Run as a Plan agent. Use EnterPlanMode before planning. Part of the Super Agent pipeline after spec registration.

Planning workflow

  1. Define objective, constraints, assumptions, and acceptance criteria.
  2. Break work into small ordered tasks with dependencies.
  3. Add exact target files or the narrowest safe path scope per task.
  4. Add explicit runnable commands and expected checkpoints per task.
  5. Add validation per task (build, tests, smoke checks).
  6. Identify risks and fallback path for each critical task.
  7. Add stable commit checkpoint suggestions for meaningful delivery slices.
  8. Produce an execution order that can be run incrementally.

Output contract

  1. Scope summary
  2. Ordered tasks with target paths, commands, and checkpoints
  3. Validation checklist
  4. Risk list and mitigation
  5. Delivery slices (incremental → final)
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 42 lines · 43 tokens per session scan A f8ae5b36aefe

Subscribe to this mod's changes

plan-task-planner is a skill published in the GitHub repository ThiagoGuislotti/copilot-instructions (2 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 343 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens