mcp-server-anydoc

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

The description reveals that conversion runs locally and on-device via anydoc, which is a meaningful behavioral trait given no annotations. However, it does not mention return format, error handling, or other side effects, leaving some behavioral aspects undisclosed.

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?

The description is two sentences, starts with the core action, and each sentence contributes distinct value: what it does, when to use, and where it runs. There is no wasted or redundant wording.

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?

For a tool with 3 parameters and no output schema, the description covers purpose, usage context, and a behavioral note. It does not explicitly describe the return value, but the conversion to Markdown implies the output. Given the simplicity, it is reasonably complete for selection and invocation.

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?

The input schema already provides complete descriptions for all 3 parameters (100% coverage), so the description adds little beyond schema. It mentions 'base64' and 'filename' but does not clarify parameter usage or dependencies beyond what the schema states.

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?

The description clearly states the tool converts base64 document bytes to Markdown locally, using a specific verb and resource. It distinguishes itself from path-based sibling tools by emphasizing the base64 input context.

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 explicit guidance on when to use the tool: when file content is already in context and a filesystem path cannot be passed. It implies when not to use it but does not name alternative tools directly, though siblings are visible in context.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states 'No API key' and 'File never leaves the device', which are important operational characteristics. It doesn't mention edge cases or side effects, but the included privacy guarantees are substantive and beyond typical.

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?

The description is four short, purposeful sentences. Each sentence adds information—action, formats, privacy, and usage preference—without any fluff or redundancy. It is front-loaded with the primary action and immediately followed by key differentiators.

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?

The tool has three parameters and no output schema, but the schema property for output_path explains the inline-vs-file output behavior. The description complements this with supported formats and privacy context. It is sufficiently complete for an agent to select and invoke the tool safely, though it could explicitly mention the return type if no output_path is given.

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?

Although the schema already describes each parameter clearly (100% coverage), the description adds value by enumerating the exact supported document formats (PDF, Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV), which clarifies what the optional 'format' parameter expects and when format hints might be needed.

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?

The description uses the specific verb 'Convert' with a clear resource ('local office document') and target format ('GitHub-Flavored Markdown'). It lists supported input types, and the stipulation to prefer it over cloud parsers distinguishes it from upload-based alternatives.

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 explicit usage context: it's for local, private conversions without an API key, and recommends it over cloud-based document parsers. However, it does not directly contrast with sibling tools like convert_base64 or list_formats, leaving some ambiguity for niche use cases.

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

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 the scope ('local anydoc MCP server') and the purpose (convert to Markdown), but it does not describe the output format, such as whether it returns names, MIME types, or extensions. This provides some context beyond the bare operation but remains minimal.

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?

The description is a single, front-loaded sentence with no filler. Every word contributes to the purpose, making it highly concise and well-structured.

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?

For a zero-parameter list tool, the description covers the core purpose and scope. However, without an output schema, it omits details about the response structure (e.g., array of strings, format types), which is a notable gap for such a simple tool. It is minimally complete but not fully informative.

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?

The tool has zero parameters, so the baseline is 4. The description adds meaning by clarifying the output is formats convertible to Markdown, though it does not discuss parameter details because none exist. This is appropriate for a parameterless 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?

The description clearly states the action ('List') and the resource ('document formats'), and adds context ('this local anydoc MCP server can convert to Markdown'), which distinguishes it from siblings convert_base64 and convert_document. It is specific and unambiguous.

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 implies the tool is used to discover which formats are supported for conversion to Markdown, but it does not explicitly state when to use it versus alternatives or mention any prerequisites. The context is somewhat clear but lacks explicit guidance.

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