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.
npx skills add itallstartedwithaidea/agent-skills --skill writing-plansgit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/writing-plans)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/writing-plans"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/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/itallstartedwithaidea/agent-skills/writing-plans"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/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 | $0.00041 | $0.01214 |
| Opus 5 | $0.00020 | $0.00607 |
| Sonnet 5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00121 |
Grade A, and why
writing-plans scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Plans include verification steps after each implementation step: a test to run, a curl command to execute, or a UI state to confirm. This tight feedback loop ensures errors are caught immediately rather than compounding How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Plans
Part of Agent Skills™ by googleadsagent.ai™
Description
Writing Plans decomposes any implementation task into a sequence of atomic steps, each completable in 2-5 minutes, with exact file paths, complete code blocks, and verification commands. The plan is a self-contained execution script that another agent—or a future version of the same agent—can follow without needing the original conversation context.
The critical distinction between a plan and a TODO list is specificity. A plan does not say "update the API handler." It says "in src/api/routes/users.ts, add a GET /users/:id/preferences handler at line 47 that returns a UserPreferences object with fields theme, locale, and notifications, validated by the preferencesSchema defined in src/api/schemas.ts." Every step is unambiguous enough to execute mechanically.
Plans include verification steps after each implementation step: a test to run, a curl command to execute, or a UI state to confirm. This tight feedback loop ensures errors are caught immediately rather than compounding across subsequent steps.
Use When
- A task involves modifying 3+ files
- The implementation path is known but the execution is non-trivial
- Work needs to be handed off to another agent or resumed later
- The user asks for a plan, roadmap, or step-by-step breakdown
- You need to estimate effort before committing to implementation
- Complex refactoring requires precise ordering of changes
How It Works
graph TD
A[Task Description] --> B[Identify Affected Files]
B --> C[Determine Change Order]
C --> D[Write Step 1: File + Code + Verify]
D --> E[Write Step 2: File + Code + Verify]
E --> F[Write Step N: File + Code + Verify]
F --> G[Add Rollback Instructions]
G --> H[Estimate Total Duration]
H --> I[Present Plan for Approval]
I -->|Approved| J[Save as plan.md]
I -->|Needs Revision| B
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.
- 5d ago First seen · 121 lines · 41 tokens per session scan A 53ec142f9da7
writing-plans is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (37 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 1,214 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
gws-gmail
Gmail: Send, read, and manage email.
recipe-block-focus-time
Create recurring focus time blocks on Google Calendar to protect deep work hours.
dws
A command-line guide for DingTalk, a workplace platform with chat, documents, calendars, approvals, tasks, and other business tools.
naver-blog-post
A guide to writing useful, search-focused information posts for Naver Blog, a Korean blogging platform and search service. It covers titles, headings, images, internal links, and checking competing posts.
self-improve
ChaosEngine Learning Session self-improve skill. Dual-track harness + product lessons via learning.py. Trigger on self-improve or learning session.
web-demo-video
A process for making product-demo videos from a real website or web app by displaying it in an embedded browser page, controlling it with real mouse events, capturing the frames, and combining them with ffmpeg.