writing-plans

writing-plans is a skill for Claude Code, Codex from math-inc/OpenGauss. It costs 36 tokens per session (1,773 once invoked), scanned A, a copy of writing-plans, MIT.

A method for turning requirements into a detailed implementation guide with small tasks, exact files, code examples, testing commands, and verification steps.

In plain words
What is it for?
It helps plan multi-step features, break work into manageable tasks, document files to change, and define how to test and verify the result.
Why use it?
It removes uncertainty for developers or coding helpers who need to implement work without knowing the codebase or problem domain well.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit It helps plan multi-step features, break work into manageable tasks, document files to change, and define how to test and verify the result.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/math-inc/opengauss/writing-plans
About the project

OpenGauss is a project-scoped Lean workflow orchestrator that gives coding agents a command-line interface for managing formal proof and formalization tasks. It is used with Lean projects to coordinate agents, tooling, backend sessions, and workflows supplied by lean4-skills. The catalogue add-ons operate these Gauss-native workflows.

math-inc/OpenGauss · 1,260 stars · on GitHub

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.

Any agent
npx skills add math-inc/OpenGauss --skill writing-plans
Clone the repo
git clone --depth 1 https://github.com/math-inc/OpenGauss

Made for: Claude Code, Codex.

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 writing-plans

README.md
[![agentmods](https://agentmods.dev/badge/skills/math-inc/opengauss/writing-plans.svg)](https://agentmods.dev/skills/math-inc/opengauss/writing-plans)
Your own site
<a href="https://agentmods.dev/skills/math-inc/opengauss/writing-plans"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/writing-plans.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,773 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod 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 $0.00036 $0.01773
Opus 5 $0.00018 $0.00886
Sonnet 5 $0.00007 $0.00355
Haiku 4.5 $0.00004 $0.00177

Measured 5d ago against content hash 7af61efa67a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

writing-plans 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.

Origin

This is a copy

91% identical to writing-plans — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/software-development/writing-plans/SKILL.md · 297 lines

How it starts

The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Writing Implementation Plans

Overview

Write comprehensive implementation plans assuming the implementer has zero context for the codebase and questionable taste. Document everything they need: which files to touch, complete code, testing commands, docs to check, how to verify. Give them bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.

Assume the implementer is a skilled developer but knows almost nothing about the toolset or problem domain. Assume they don't know good test design very well.

Core principle: A good plan makes implementation obvious. If someone has to guess, the plan is incomplete.

When to Use

Always use before:

  • Implementing multi-step features
  • Breaking down complex requirements
  • Delegating to subagents via subagent-driven-development

Don't skip when:

  • Feature seems simple (assumptions cause bugs)
  • You plan to implement it yourself (future you needs guidance)
  • Working alone (documentation matters)

Bite-Sized Task Granularity

Each task = 2-5 minutes of focused work.

Every step is one action:

  • "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

Too big:

### Task 1: Build authentication system
[50 lines of code across 5 files]

Right size:

### Task 1: Create User model with email field
[10 lines, 1 file]

### Task 2: Add password hash field to User
[8 lines, 1 file]

### Task 3: Create password hashing utility
[15 lines, 1 file]

Plan Document Structure

Header (Required)

Every plan MUST start with:

# [Feature Name] Implementation Plan

> **For Gauss:** Use subagent-driven-development skill to implement this plan task-by-task.

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

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

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

---

Task Structure

Read the full file on GitHub · 297 lines

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 · 297 lines · 36 tokens per session scan A 7af61efa67a0

Subscribe to this mod's changes

writing-plans is a skill published in the GitHub repository math-inc/OpenGauss (1,260 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 1,773 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to writing-plans, differing in 11 lines, and is treated as a copy.

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

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

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 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