rdocx: Skill for Codex

.agents/skills/design/SKILL.md

design is a skill for Codex from tensorbee/rdocx. It costs 17 tokens per session (178 once invoked), scanned A, a copy of close-sprint, MIT.

A workflow for designing a feature before writing code. It produces a design plan and makes no code changes.

In plain words
What is it for?
Use it to plan a feature and record its intended design before development.
Why use it?
It helps clarify the approach and requirements before implementation begins.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: reads .claude/ paths; names the AskUserQuestion tool; installed under .agents/ (shared by several agents).

This is tensorbee/rdocx's own configuration. It tells Codex how to work on rdocx itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything rdocx configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tensorbee/rdocx. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/tensorbee/rdocx/main/.agents/skills/design/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/tensorbee/rdocx

Made for: 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 design

README.md
[![agentmods](https://agentmods.dev/badge/skills/tensorbee/rdocx/design/github.svg)](https://agentmods.dev/skills/tensorbee/rdocx/design)
Your own site
<a href="https://agentmods.dev/skills/tensorbee/rdocx/design"><img src="https://agentmods.dev/badge/skills/tensorbee/rdocx/design/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.

agentmods 80×15 button for design

Your own site · 80×15
<a href="https://agentmods.dev/skills/tensorbee/rdocx/design"><img src="https://agentmods.dev/badge/skills/tensorbee/rdocx/design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 178 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 88% 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 $0.00017 $0.00178
Opus 5.5 $0.00007 $0.00071
Sonnet 5.5 $0.00003 $0.00036
Haiku 4.5 $0.00002 $0.00018

Measured 6d ago against content hash effab39de849, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

design 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 6d 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

88% identical to close-sprint — 8 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.

.agents/skills/design/SKILL.md · 13 lines

What it actually says

Canonical source: .claude/commands/design.md.

Source SHA-256: 4200a5757cddf34660e649d3cf88c6e16f509324eed75745dfca30208becccd4.

Read the canonical source in full before acting, and follow it with whatever tools this host provides. Treat any invocation arguments as arguments to that workflow. Where it names another slash command, follow the repository skill of the same name. Where it says to ask with AskUserQuestion, ask through this host's own question mechanism. .claude/WORKFLOW.md wins on any process question. Do not edit this generated adapter.

Files

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.

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. 6d ago Changed effab39de849
  2. 11d ago Changed 8e017922f67e
  3. 26d ago First seen · 13 lines · 17 tokens per session scan A 24489231eb40

Subscribe to this mod's changes

design is a skill published in the GitHub repository tensorbee/rdocx (44 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 178 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to close-sprint, differing in 8 lines, and is treated as a copy.

Related

Other skills, from other repositories

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

systematic-debugging

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

obra/superpowers · 21 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

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

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens