Chunk web page for RAG

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

Annotations declare readOnlyHint and openWorldHint, so safety and network scope are covered. The description adds that only main content is chunked and that chunks carry heading path and token count, which is useful beyond annotations, but says nothing about failure modes (unreachable URL, robots restrictions) or content types.

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 tightly packed sentences with no filler; the core action and the output shape are front-loaded. Every clause earns its place.

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?

No output schema exists, yet the description fills that gap by describing the returned chunk structure (heading path, token count). Combined with full schema coverage and annotations, an agent has nearly everything needed, though error/edge-case behavior remains unstated.

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 description coverage is 100%, so the schema fully documents all six parameters including defaults and ranges. The description only echoes the chunk-size and heading concepts, adding no semantics the schema does not already provide. Baseline 3 applies.

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?

Precise verb-and-resource plus the transformation intent: fetch a page, split main content into heading-aware, token-bounded chunks for RAG/embeddings. This clearly distinguishes it from read_url (raw content) and convert_html (format conversion).

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?

The stated purpose ('for RAG/embeddings') implies when to use it, but it never names alternatives like read_url or convert_html or states when not to use chunking. Usage is inferred rather than directed.

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