convert_document_to_markdown

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

With no annotations, the description carries the full burden and delivers useful traits: pure local execution, no API key, no network calls, no OCR, and no rendering of embedded images. These are meaningful behavioral facts an agent needs before invoking. It does not describe error behavior or output shape in detail, keeping it short of a 5.

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?

Front-loaded with the core action, then format support, then operating constraints and caveats, all in a compact block. The format enumeration is long but earns its place by defining accepted inputs.

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, but the description implies the return format (GFM) and flags key limitations. Combined with 100% schema coverage and full required-parameter documentation, an agent has enough to call it correctly; only error/edge-case handling is left 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 already documents both parameters (filename for format detection, base64 content). The description adds no per-parameter detail beyond what the schema provides, so the 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?

States a specific verb+resource ('convert documents to clean GitHub-Flavored Markdown') and enumerates every supported input format, so an agent immediately knows the operation and its scope. There are no siblings to distinguish from, and the naming of the underlying engine (anydoc) adds specificity.

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 description gives clear negative guidance ('scanned/image PDFs not supported', 'no OCR'), which functions as a when-not-to-use rule and steers the agent away from unsupported inputs. It lacks explicit routing to alternatives, but no sibling tools exist, so the context coverage is strong.

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