agent-from-docs

A command that creates a specialized AI agent from one or more documentation web addresses. It researches the documented technology, including its concepts, APIs, conventions, workflows, and implementation details.

In plain words
What is it for?
Analyzing documentation URLs and preparing the knowledge needed to create a focused development agent.
Why use it?
It turns scattered technical documentation into the research needed to define an agent for a specific technology.

Command for Claude Code

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.

agentmods
npx agentmods add commands/nodnarbnitram/claude-code-extensions/agent-from-docs
Clone the repo
git clone --depth 1 https://github.com/nodnarbnitram/claude-code-extensions

Made for: Claude Code.

Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 975 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00008 $0.00975
Opus 5 $0.00004 $0.00487
Sonnet 5 $0.00002 $0.00195
Haiku 4.5 $0.00001 $0.00097

Measured 2d ago against content hash 79b728634a83, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-from-docs 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 2d 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.

.claude/commands/agent-from-docs.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Agent from Documentation

You will create a new specialized agent by analyzing documentation from the provided URLs.

Documentation URLs: $ARGUMENTS

Your Task

Follow these steps to create the agent:

Step 1: Analyze Documentation

If multiple URLs are provided, launch multiple technical-researcher agents in parallel (one per URL). If only one URL is provided, use a single researcher.

For parallel execution with multiple URLs:

  • Launch all technical-researcher agents simultaneously in a single message with multiple Task tool calls
  • Each agent should analyze its assigned URL independently
  • Combine all research findings before proceeding to Step 2

Each researcher should investigate:

  • What technology/framework/library is being documented
  • Key concepts, APIs, methods, and patterns
  • Best practices and conventions
  • Common workflows and use cases
  • Important implementation details that an expert should know
  • How this technology differs from alternatives

Request a comprehensive summary suitable for creating a specialized agent.

Step 1.5: Determine Agent Creation Strategy

After gathering all research findings, analyze whether to create one or multiple agents:

Create MULTIPLE agents when URLs represent distinct verticals/technologies:

  • Different core APIs or services (e.g., Cloudflare Workers vs D1 vs R2)
  • Separate deployment models or runtime environments
  • Distinct problem domains within a platform
  • Independent tools/products that happen to share a brand

Create a SINGLE agent when URLs cover the same technology:

  • Different aspects of one framework (e.g., Next.js routing + data fetching + deployment)
  • Progressive documentation depth on one topic
  • Multiple guides for the same library/tool

Examples:

  • ✅ Multiple agents: workers.cloudflare.com/docs + developers.cloudflare.com/d1 + developers.cloudflare.com/r2 → 3 specialized agents
  • ❌ Single agent: nextjs.org/docs/routing + nextjs.org/docs/api-routes + nextjs.org/docs/deployment → 1 comprehensive agent

Read the full file on GitHub · 108 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. 2d ago First seen · 108 lines · 8 tokens per session scan A 79b728634a83

Subscribe to this mod's changes

agent-from-docs is a command published in the GitHub repository nodnarbnitram/claude-code-extensions (16 stars, last pushed 4mo ago), licensed MIT. It adds 8 tokens to every session and 975 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.