Borrowing it
Nothing to install: this file belongs to mdcms-ai/mdcms. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mdcms-ai/mdcms/main/.ai/skills/writing-plans/SKILL.mdgit clone --depth 1 https://github.com/mdcms-ai/mdcmsWrote 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.
[](https://agentmods.dev/skills/mdcms-ai/mdcms/writing-plans)<a href="https://agentmods.dev/skills/mdcms-ai/mdcms/writing-plans"><img src="https://agentmods.dev/badge/skills/mdcms-ai/mdcms/writing-plans/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mdcms-ai/mdcms/writing-plans"><img src="https://agentmods.dev/badge/skills/mdcms-ai/mdcms/writing-plans.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.01380 |
| Opus 5.5 | $0.00008 | $0.00552 |
| Sonnet 5.5 | $0.00004 | $0.00276 |
| Haiku 4.5 | $0.00002 | $0.00138 |
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 2mo 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.
This is a copy
80% identical to writing-plans — 122 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.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Plans
Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
Announce at start: "I'm using the writing-plans skill to create the implementation plan."
Context: This should be run in a dedicated worktree (created by brainstorming skill).
Save plans to: .ai/plans/YYYY-MM-DD-<feature-name>.md
- (User preferences for plan location override this default)
Scope Check
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
File Structure
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
- Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
- You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
- Files that change together should live together. Split by responsibility, not by technical layer.
- In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 153 lines · 21 tokens per session scan A 2a1342223323
writing-plans is a skill published in the GitHub repository mdcms-ai/mdcms (22 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 1,380 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 80% identical to writing-plans, differing in 122 lines, and is treated as a copy.
Other skills, from other repositories
review
Review one pull request for real bugs, regressions, and convention violations. Enumerate candidate issues across the whole diff, verify each against the code, then return structured line-anchored findings and a verdict. Read-only on GitHub; the orchestrator posts the review.
creating-plugins
Create EmDash CMS plugins with sandboxed hooks, routes, storage, content and media APIs, MCP tools, and declarative admin UI, or native React and Astro extensions. Use when scaffolding or implementing an EmDash plugin.
emdash-cli
Use the EmDash CLI to inspect and manage an EmDash instance from the command line, including content, schema, media, taxonomies, menus, search, authentication, seeds, migrations, generated types, and whole-site export and import.
building-emdash-site
Build the site-facing parts of an EmDash CMS project on Astro, including schema and seeds, content queries, Portable Text rendering, menus, taxonomies, widgets, and deployment configuration. Use for EmDash site and theme work; use creating-plugins instead when the task is plugin authoring alone.
writing-emdash-docs
Write, revise, and review EmDash documentation for technical accuracy, useful structure, house style, and natural prose. Use when working on user documentation, guides, API reference pages, migration or upgrade guides, READMEs, contributor documentation, technical specifications, or release notes in the EmDash…
ux-acceptance-coordinator
Coordinate black-box, agent-driven UX acceptance journeys against a disposable EmDash admin site. Use when preparing, dispatching, verifying, or reporting a manual browser journey performed by a separate tester agent. Do not use for deterministic Playwright tests or ordinary code review.