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AgentDiet Automated /llms.txt & Agent Documentation Context Compiler

by dev.agentdiet
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generate_site_llms_txt

Read-onlyIdempotent

Crawls any documentation or SaaS site and compiles a standards-compliant /llms.txt manifest and JSON-LD schema bundle. WHEN TO USE: Call generate_site_llms_txt when your task requires deterministic llms-generator analysis for url; use get_agent_wallet_status to check your remaining free trial quota or prepaid balance. WHEN NOT TO USE: Do not use for unrelated domains or binary media. PARAMETER INTERACTIONS: Pass the target url as a non-empty string; omit agent_id and tx_hash during your 5 free trial calls, or supply agent_id (agd_pass_...) / tx_hash for paid execution. Read-only and idempotent; results are cached for 1 hour (<5ms cache hit). $0.015 per call. Pricing: the first 5 calls per agent_id are free and failed calls are never charged. After 5 calls, the tool returns a payment-required quote (not a fatal error) with a $2 Stripe top-up link and Base/Solana USDC addresses; complete payment, then retry with your agd_pass_ key in agent_id or pass tx_hash. Example: generate_site_llms_txt(url='https://docs.stripe.com/api')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL to crawl and generate a ready-to-consume /llms.txt manifest for.
tx_hashNoOptional on-chain Base Mainnet (0x...) or Solana SPL USDC transaction hash. Omit unless settling an individual call directly on-chain instead of using an agd_pass_ key in agent_id.
agent_idNoOptional agent identifier or prepaid agd_pass_ session key. Omit during your 5 free trial calls to use an ID automatically derived from your client IP, or pass your agd_pass_ key after topping up.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoStructured tool output payload.
statusYesExecution status ('ok' or 'payment_required').
roi_proofNoToken compression and cost-savings verification metrics.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover readOnly/idempotent, and the description goes well beyond them: 1-hour cache with <5ms hits, $0.015 per call, 5 free calls per agent_id, failed calls never charged, and a payment-required quote returned as a non-fatal result with top-up instructions. This is the kind of operational detail annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded purpose then clearly labeled WHEN/WITHOUT/PARAMETER sections; the example anchors usage. Mild redundancy in the pricing passage, which restates the free-call and per-call cost in two separate places.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation. Coverage of crawl scope, caching, billing lifecycle, and failure behavior makes the definition fully sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and per-parameter descriptions are already detailed, so the baseline is 3. The description adds genuine interaction semantics (omit agent_id/tx_hash during free calls, supply either afterward) rather than repeating field docs, but much of that logic is mirrored in the schema text, limiting added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb pair (crawls, compiles) plus concrete artifacts: a standards-compliant /llms.txt manifest and JSON-LD schema bundle. It explicitly names the sibling get_agent_wallet_status and assigns it a different job, so an agent can separate the two without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit WHEN TO USE / WHEN NOT TO USE sections, including the condition that selects the sibling (quota/balance checks) and the exclusion for unrelated domains and binary media. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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