read_doc_markdown

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

No annotations provided, so description carries full burden. Discloses token savings (~60%), placeholder format for images/files, and refers to download_doc_image for binaries. Does not describe rate limits or auth needs, but these are likely minimal for a read operation.

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 plugin version and main purpose, then key differentiators and specifics. Every sentence adds value with no redundancy.

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 one parameter, no output schema, and no annotations, description covers input formats, output representation (markdown with placeholders), token efficiency, and correlation with sibling tool download_doc_image. Fully sufficient for agent to use correctly.

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 100% with one parameter 'document_id' described as 'docx token / wiki node / full URL'. Description adds value by clarifying acceptable input types beyond the schema's brief description.

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?

Description clearly states it reads a Feishu doc as Markdown, distinguishes from get_doc_blocks (JSON), and specifies use cases like RAG/digest/summarisation. Verb+resource+scope are specific.

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?

Explicitly mentions when to use (to save tokens vs JSON format), suggests alternative tool (get_doc_blocks), and lists acceptable input formats (docx token, wiki node, full UKL).

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