converter

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

With no annotations, the description carries the burden and does disclose meaningful behavior: the tool returns the conversion engine, AI Deep Read need, accepted options, and fallback alternatives; it also explains accepted format identifiers. It does not explicitly state that the tool performs no conversion, but the 'before sending' phrasing strongly implies a non-mutating check.

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?

Three sentences, each earning its place: purpose is front-loaded, returns are listed, and the format-input quirk is included. 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?

The description is sufficient for a read-only preflight tool with two simple parameters. It names the key return fields and the accepted input forms; it doesn't need an output schema because there isn't one and the textual coverage is adequate.

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 schema already describes the two params at 100% coverage, so baseline is 3. The description adds real value by explaining that values can be ids, extensions, or common names—information not present in the schema—which helps an agent construct correct inputs.

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 states a specific action—'Check whether one format can be converted to another'—and clearly distinguishes it from siblings like convert_file by noting it's done 'before sending a file.' It also lists the concrete output (engine, AI Deep Read need, options, alternatives), so an agent can tell exactly what this tool does.

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?

It tells the agent when to use it ('before sending a file'), which implies it precedes convert_file. However, it never names sibling alternatives or explains when to prefer list_formats/get_conversion, so it stops short of explicit when-not guidance.

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 carrying the burden, the description is unusually transparent: it states output size thresholds, inline text vs base64/downloadUrl behavior, bearer-token reuse, the 10 MB input limit, and the per-page credit cost of deepRead. This gives an agent accurate expectations before calling.

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 dense sentences with no filler: it front-loads the action, then follows with input constraints, output behavior, size limits, and deepRead cost in logical order. Every sentence 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?

For a 7-parameter tool with no output schema and no annotations, the description covers input modes, limits, output delivery, authentication-sensitive download behavior, and optional AI deep-read cost. Combined with full schema coverage, an agent has everything needed to invoke the tool 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?

Even though schema coverage is 100%, the description adds meaningful relationships beyond the terse schema: base64 and url are alternatives, `from` is inferred from filename/URL extension, deepRead means OCR+layout understanding with credit cost, and output representation depends on format and size. These clarifications materially improve parameter understanding.

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 opens with a specific verb and resource: 'Convert a file', and the surrounding detail makes clear this is the execution tool for conversions. It is distinguishable from the check/get/list siblings by intent, but it never explicitly names or contrasts those siblings.

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 strong invocation guidance: provide base64 OR a public URL, omit `from` when an extension is present, keep files under 10 MB, and use deepRead for scans/photos/handwriting. However, it does not explicitly say when to choose convert_file over the sibling tools like check_conversion or get_conversion.

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 behavioral burden. It usefully discloses that output is only included 'if it is still retained', implying retention limits, and that the operation is a fetch. However, it does not address error behavior, authentication, or response shape beyond the listed fields.

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?

A single, front-loaded sentence contains the verb, resource, retrieval criteria, and return contents with no wasted words. It is appropriately sized for a simple fetch operation.

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 one-parameter read operation with no output schema and no annotations, the description covers the key information: what to pass, what will be returned, and the retention caveat. It is slightly limited by not addressing alternatives or errors, but it is otherwise complete for a tool of this complexity.

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 schema only defines 'id' as a string with 0% coverage, so the description must compensate. It adds the meaning that id refers to a previous conversion, which is helpful, but it does not clarify id format, source, or how to obtain it. For a single simple parameter this is adequate but not rich.

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 verb 'Fetch' and the resource 'a previous conversion by id', and lists what is returned: status, warnings, and output if retained. It does not explicitly distinguish itself from the sibling check_conversion, but the mention of retrieving the output makes the primary purpose clear.

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?

There is no explicit guidance about when to use this tool versus siblings such as check_conversion or convert_file. The description implies use for retrieving an existing conversion, but it does not state exclusions or alternatives, leaving routing decisions to inference.

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 exist, so the description carries the disclosure burden. It does reveal the return shape ({from,to,slug,engine,mode}) and the bidirectional query mode, which is useful. However, it does not disclose behavior when both to and from are provided, empty results, or error handling.

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?

One concise sentence front-loads the purpose and immediately follows with the return shape. Every word earns its place and there is no redundant boilerplate.

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 no annotations, no output schema, and undocumented parameters, the description is too thin. It omits how the optional to/from parameters interact, what format identifiers look like, and how this relates to sibling tools, so an agent cannot reliably call it 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 description coverage is 0% and the schema only declares optional string properties. The description maps from/to to source/target conceptually, but provides no value formats, examples, or combination rules, leaving the agent to guess valid input.

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 states a specific verb ('List') and resource (supported target formats for a source format), and clarifies the reverse direction. It is distinguishable from siblings like convert_file and list_formats, though it does not name them explicitly.

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 this is the enumeration endpoint for conversion options, but it never states when to prefer it over check_conversion, get_conversion, or list_formats. No exclusions or alternative routing are provided.

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, the description must carry behavioral transparency. It implies a read-only enumeration of format metadata, which is sufficient for a low-risk listing tool, but it does not explicitly state that it never modifies data or whether any authentication is required.

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 short sentences with no filler. The first sentence describes the resource and fields; the second gives actionable usage guidance. The most important information is front-loaded.

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 listing tool with no output schema, the description covers what the tool returns (id, name, extensions, family) and how to use those values. Nothing critical is missing for correct 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 tool has zero parameters and the schema is fully described, so the baseline is 4. The description adds value by explaining that the output `id` values are intended for use in other tools, which is useful context even though no parameters exist here.

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 states a specific verb ('List') and resource ('every file format this converter reads or writes'), and names the returned fields (id, name, extensions, family). This clearly separates it from the sibling conversion-specific tools like convert_file and list_conversions.

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 second sentence gives explicit guidance: use the id values as `from`/`to` in other tools, which tells the agent how to apply the result. It does not explicitly name sibling tools or state when not to use it, but the context is clear.

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