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Read The Damn Docs

OrganizationPopular
BuilderIO
read-the-damn-docs

Use when implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model/provider SDKs, fast-moving product behavior, user requests for latest/current/official behavior, unfamiliar repo docs/specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces Codex to web-search for current official docs and read primary docs before assuming from memory.

Overview

PublisherBuilderIO
Repositoryskills
Skill nameread-the-damn-docs
Stars
4.3K
Forks
211
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by BuilderIO on GitHub. Read the source before you install it.

Installation

Install the Read The Damn Docs AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/BuilderIO/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/read-the-damn-docs .claude/skills/read-the-damn-docs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Read The Damn Docs in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Read The Damn Docs on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Read The Damn Docs is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Read The Damn Docs

Do not guess where authoritative docs can answer the question. The most common right move is to web-search for the current official docs, open the relevant pages, and read them before coding. For APIs, versions, provider behavior, config, limits, lifecycle hooks, or security-sensitive flows, ground the answer in what the docs actually say.

Docs-First Triggers

Read docs before proceeding when any of these are true:

  • The user asks for "latest", "current", "official", "supported", "best practice", "recommended", "today", "now", or "look it up".
  • The needed docs are not already in the repo or supplied by the user. Search the web for the official docs rather than hoping model memory is current.
  • The task adds, upgrades, configures, or imports a package, SDK, framework, plugin, CLI, model, cloud resource, or provider integration.
  • The API is fast-moving or version-sensitive: AI SDKs, OpenAI/Anthropic/Google APIs, Next.js, React, Tailwind, Vite, Nitro, Drizzle, Prisma, Stripe, GitHub, Slack, Notion, browser APIs, deployment platforms, auth libraries, and similar.
  • The implementation depends on auth, OAuth scopes, permissions, secrets, webhooks, billing, payments, PII, encryption, data retention, migrations, retries, rate limits, quotas, caching, deploys, or compliance.
  • An error mentions deprecation, unknown options, missing exports, invalid config, unsupported fields, changed defaults, or version mismatch.
  • A repo has local docs, ADRs, generated schemas, OpenAPI specs, route/action registries, design-system docs, or package-level READMEs that could define the contract.
  • The choice is expensive to reverse: public wire formats, database schema, migration strategy, persistent IDs, event names, customer-visible behavior, or external automation contracts.
  • You catch yourself about to write "usually", "probably", "I think", "from memory", or code copied from model memory for an external API.

What Counts As Docs

Use the most authoritative source available:

  • Local repo docs, specs, ADRs, schemas, generated types, package READMEs, and tests for project-specific behavior.
  • Official product docs, API references, migration guides, changelogs, release notes, and SDK source/types for third-party behavior. Find these with web search when you do not already have the exact URL.
  • Package registry metadata for versions. Before adding a dependency, run npm view <pkg> version, pnpm view <pkg> version, or the ecosystem equivalent, then read the docs for that major version.
  • Source code or type definitions when official docs are incomplete. Treat this as evidence, not folklore.

Avoid Stack Overflow, old blog posts, random snippets, and memory as the primary source when official docs exist. Use community sources only to debug symptoms after the authoritative contract is known.

Required Workflow

  1. Identify the exact surface: package name, installed version, target version, provider endpoint, CLI command, config file, local helper, schema, or product feature.
  2. Search the web for the current official docs unless the relevant docs are already local or the user supplied a URL. Use targeted searches such as <product> <feature> official docs, <package> migration guide, or <provider> API reference.
  3. Open and read the docs closest to that surface. Prefer local docs first for internal code, then official upstream docs. For new packages, verify the latest version before writing imports, config, or install commands.
  4. Extract the few facts needed for the task: option names, imports, lifecycle rules, default behavior, breaking changes, limits, permissions, and examples for the current major version.
  5. Implement or answer using those facts. If the docs conflict with existing code, inspect the local code path and call out the discrepancy.
  6. Verify with the smallest useful check: typecheck, tests, build, CLI dry run, API schema validation, or a local reproduction.
  7. In the final answer, name the docs or local files consulted when that evidence affects the recommendation or implementation.

Examples That Must Trigger Docs

  • "Add Tailwind to this app." Check the current Tailwind major and its install docs from the web before creating config files or assuming old PostCSS setup.
  • "Use the AI SDK to stream responses." Verify the current AI SDK major, imports, provider package names, streaming helpers, and server/runtime examples from official docs.
  • "Wire up Stripe webhooks." Read Stripe's current signature verification, event retry, endpoint secret, and framework body-parsing docs before coding.
  • "Fix this Next.js caching bug." Read the docs for the installed Next.js major and router mode before assuming cache invalidation semantics.
  • "Add Drizzle migrations." Read the current Drizzle kit docs and existing repo migration conventions before generating files.
  • "Create a GitHub Action." Read official Actions syntax and permissions docs, especially for pull_request, workflow_run, OIDC, tokens, and artifacts.
  • "Why does this OAuth flow fail?" Read the provider's scopes, redirect URI, PKCE, token refresh, and app verification docs before changing code.
  • "Use this repo's plan/comment/action system." Read local docs, route/action registries, schemas, and tests before inventing endpoints or props.
  • "Upgrade Vite/Nitro/React." Read the migration guide for the exact target major before editing config or imports.
  • "What model should we use?" Read current provider model docs, pricing/limits pages, and SDK examples before recommending.

When A Quick Local Read Is Enough

Do not browse the web for every tiny edit. A docs pass can be local and brief when the answer is already in the repo: existing helper usage, nearby tests, typed interfaces, generated clients, ADRs, or package READMEs. But if the task depends on an external tool, package, provider, or current product behavior, web search is usually the right first step. For trivial language syntax, typo fixes, formatting, or self-contained code with no external contract, proceed normally.

If Docs Are Unavailable

If network access, auth, or missing local files prevents reading the docs, say that plainly before relying on memory. Narrow the uncertainty, inspect source or types if available, and avoid presenting the result as confirmed-current.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Read The Damn Docs AI skill do?

Use when implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model/provider SDKs, fast-moving product behavior, user requests for latest/current/official behavior, unfamiliar repo docs/specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces Codex to web-search for current official docs and read primary docs before assuming from memory.

Why use Read The Damn Docs on TypingMind?

Because you install it once and use it with any model. Read The Damn Docs is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Read The Damn Docs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BuilderIO/skills/tree/main/skills/read-the-damn-docs. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Read The Damn Docs?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Read The Damn Docs?

As many as you like. As long as a model supports skills, you can use Read The Damn Docs with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Read The Damn Docs AI skill free?

Yes. It is published on GitHub by BuilderIO under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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