Agent skill

Writing Plans

by itseffi in itseffi/agentic-os

Create comprehensive implementation plans with bite-sized tasks.

MITAuto-check passedAgent Workflows

Install Writing Plans

skills CLI
$ npx skills add itseffi/agentic-os --skill writing-plans -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install itseffi/agentic-os writing-plans --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/itseffi/agentic-os.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/writing-plans .claude/skills/writing-plans && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
writing-plans
GitHub stars
115
Token cost
~547 tokens
SKILL.md length
135 words
Files
2
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Create comprehensive implementation plans with bite-sized tasks.

  • You have requirements before touching code
  • SKILL.md covers Overview, Bite-Sized Task Granularity, Plan Document Header and Task Structure
  • Calls git and pytest
  • Tasks that involve Planning

What it does

Writing Plans is an agent skill from itseffi/agentic-os. Create comprehensive implementation plans with bite-sized tasks. Use when you have requirements before touching code.

Its SKILL.md is about 550 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Agent Workflows, covering Planning. The repository describes itself as: Agentic personal OS to automate high-leverage workflows with Codex, Claude Code, Pi, OpenClaw and other coding agents/ runtime platforms. The licence is MIT.

When your agent uses it

  • You have requirements before touching code
  • Tasks that involve Planning

Example prompts

  • “/writing-plans”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit e54d0ac. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git
    • pytest

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Writing Plans loads about 547 tokens when it runs. Until then it costs about 33 tokens; SKILL.md has 135 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~33
When it runs · the whole SKILL.md, loaded when a task matches
~547

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from itseffi/agentic-os at commit e54d0ac, republished under its MIT licence (© itseffi). 135 words, ~547 tokens.

Download SKILL.mdSave it as .claude/skills/writing-plans/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
writing-plans
description
Create comprehensive implementation plans with bite-sized tasks. Use when you have requirements before touching code.

Writing Plans

Use when you have requirements for a multi-step task, before touching code.

Overview

Write comprehensive implementation plans assuming the reader has zero context. Document everything: which files to touch, code snippets, testing steps, verification commands. Break into bite-sized tasks.

Bite-Sized Task Granularity

Each step is one action (2-5 minutes):

  • "Write the failing test" - step
  • "Run it to make sure it fails" - step
  • "Implement the minimal code to make the test pass" - step
  • "Run the tests and make sure they pass" - step
  • "Commit" - step

Plan Document Header

Every plan should start with:

markdown
# [Feature Name] Implementation Plan

**Goal:** [One sentence describing what this builds]

**Architecture:** [2-3 sentences about approach]

**Tech Stack:** [Key technologies/libraries]

---

Task Structure

markdown
### Task N: [Component Name]

**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`

**Step 1: Write the failing test**

```python
def test_specific_behavior():
    result = function(input)
    assert result == expected

Step 2: Run test to verify it fails

Run: pytest tests/path/test.py::test_name -v Expected: FAIL with "function not defined"

Step 3: Write minimal implementation

python
def function(input):
    return expected

Step 4: Run test to verify it passes

Run: pytest tests/path/test.py::test_name -v Expected: PASS

Step 5: Commit

bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"

## Remember

- Exact file paths always
- Complete code in plan (not "add validation")
- Exact commands with expected output
- DRY, YAGNI, TDD, frequent commits

## When to Use

Use this skill when the task directly matches the workflow described above.

## When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

© itseffi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .agents/skills/writing-plans of itseffi/agentic-os.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit e54d0ac

Compare with similar skills

Writing Plans next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Writing Plans compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Writing Plans this skillitseffi/agentic-os115—~547Automated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills103k6 repos~3.8kAutomated safety check: PassMIT
OpenSpec Guided OnboardingFission-AI/OpenSpec71k1 repos~4.5kAutomated safety check: PassMIT
Writing Plansgeeksblabla/stateofdev.ma16357 repos~661Automated safety check: PassNone
Subagent Driven DevelopmentAsvarox/allkaraoke26137 repos~1.2kAutomated safety check: PassNone

Similar skills

  • Executing Plans Inline

    obra/superpowers

    Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.

    297k GitHub starsUsed in 2 repos~5.1k tokens
    Agent WorkflowsAuto-check passed
  • Interview Me

    addyosmani/agent-skills

    Asks one question at a time, each with a best guess attached, until the agent is about 95 percent sure what you really want, before any plan, spec or code.

    103k GitHub starsUsed in 6 repos~3.8k tokens
    Agent WorkflowsAuto-check passed
  • OpenSpec Guided Onboarding

    Fission-AI/OpenSpec

    Walks you through a complete OpenSpec workflow cycle with narration while doing real work in your codebase.

    71k GitHub starsUsed in 1 repo~4.5k tokens
    Agent WorkflowsAuto-check passed
  • Writing Plans

    geeksblabla/stateofdev.ma

    A skill your agent uses when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file…

    163 GitHub starsUsed in 57 repos~661 tokens
    Agent WorkflowsAuto-check passed
  • Subagent Driven Development

    Asvarox/allkaraoke

    A skill your agent uses when executing implementation plans with independent tasks in the current session

    261 GitHub starsUsed in 37 repos~1.2k tokens
    Agent WorkflowsAuto-check passed
  • Planning With Files

    jd-opensource/JoySafeter

    Implements Manus-style file-based planning for complex tasks.

    313 GitHub starsUsed in 19 repos~1.8k tokens
    Agent WorkflowsAuto-check: notes

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Categories

Questions about Writing Plans

What does Writing Plans do?

Create comprehensive implementation plans with bite-sized tasks. Writing Plans is an agent skill from itseffi/agentic-os. Create comprehensive implementation plans with bite-sized tasks.

When should I use Writing Plans?

Writing Plans fits situations like: you have requirements before touching code; tasks that involve Planning.

How do I install Writing Plans in Claude Code?

Run `npx skills add itseffi/agentic-os --skill writing-plans -a claude-code`. Or copy the skill folder (.agents/skills/writing-plans in itseffi/agentic-os) into .claude/skills/writing-plans in your project. Claude Code loads it when a task matches its description.

How do I install Writing Plans in Codex?

Run `npx skills add itseffi/agentic-os --skill writing-plans -a codex`. Or copy the skill folder (.agents/skills/writing-plans in itseffi/agentic-os) into .agents/skills/writing-plans in your project. Codex loads it when a task matches its description.

Can I use Writing Plans in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add itseffi/agentic-os --skill writing-plans -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/writing-plans, .gemini/skills/writing-plans, .github/skills/writing-plans and .opencode/skills/writing-plans in your project.

What does Writing Plans need to run?

Going by SKILL.md and its folder, Writing Plans needs the command-line tools its instructions call (git and pytest). Our summary lists: Python 3.

Does Writing Plans access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Writing Plans safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Writing Plans use?

Writing Plans is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Writing Plans use?

About 547 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Writing Plans?

Skills that share tags, products or a category with Writing Plans: Executing Plans Inline (obra/superpowers, 297k stars), Interview Me (addyosmani/agent-skills, 103k stars), OpenSpec Guided Onboarding (Fission-AI/OpenSpec, 71k stars) and Writing Plans (geeksblabla/stateofdev.ma, 163 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Writing Plans?

itseffi (a GitHub user) maintains it in itseffi/agentic-os, which has 115 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 7, 2026.

Source: itseffi/agentic-os on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.