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

No annotations are provided, so the description carries the full burden. It discloses two important traits: no network access (no SSRF, deterministic) and a fixed per-call cost of $0.001 USDC via x402. It does not cover error behavior, size limits, or what 'normalized' means, so the disclosure is partial.

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

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

Two sentences, front-loaded with the core capability and immediately followed by use cases and the constraint. Slightly dense packing of RAG/LLM jargon, but every clause earns its place; no filler.

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

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

Given no annotations, no output schema, and 0% schema coverage, the description covers the essentials (input, scope, cost) but omits output shape (prose vs. structured), error handling, and the exact meaning of 'normalized'. Adequate for a simple transform but not complete.

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

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

Schema coverage is 0% and only one parameter ('html') exists. The description implies the input is a raw HTML document but adds no size limits, encoding requirement, or format constraints beyond what the schema's maxLength already encodes. Baseline 3 is appropriate for a single-parameter tool.

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

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

States a specific verb and resource ('Extract clean normalized text from a raw HTML document') and adds the key scope constraint 'without network access', which distinguishes it from network-fetching siblings like web-reader or canonical-web-scrape. An agent can immediately tell this is a pure local transform.

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

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

Gives explicit usage contexts (HTML-to-text conversion, document text extraction, LLM context prep, RAG ingestion) with a clear implied 'when-not' via the no-network clause. It does not explicitly name sibling alternatives such as html-to-markdown or extract-article, so 4 rather than 5.

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