DOCX.now MCP Server

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false), the description discloses the real operational constraints: the URL must be publicly accessible, private-network targets are rejected (SSRF guard), and embedded credentials are rejected — inputs an agent would otherwise only discover by failing. It stops short of noting that each call creates a new job (relevant given idempotentHint=false) or what happens on converter failure.

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 tight sentence with the action front-loaded and the restrictive constraint (public URL) placed before the rejection rule it explains. No filler. It is arguably too terse for nine parameters, but nothing present is wasted.

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 nine-parameter, open-world, non-idempotent conversion tool with 0% schema descriptions, the description covers only the two required inputs. An output schema exists so return values need no explanation, but an agent still cannot judge what quality, dimensions, strip_metadata, or timeout_seconds do, nor what the non-waiting path yields.

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% across 9 parameters, so the description carries the full burden. It explains source_url (publicly accessible, no private ranges, no credentials) and converter (a slug), and alludes to wait_for_completion, but says nothing about width, height, quality, background_color, strip_metadata, or timeout_seconds — six undocumented knobs, several of which materially change output.

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 gives a specific verb chain (download URL -> submit to DOCX.now -> optionally wait) and names the required converter slug, which is far more than a restatement of the name. It does not reconcile the mismatch between the name 'convert_image_url' and the DOCX-document framing, nor does it name the sibling tools it complements (list_converters, get_conversion_status). An agent knows the operation but not precisely which file/media types are in scope.

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?

'optionally wait for the result' hints that wait_for_completion=false is the path to poll via get_conversion_status, but the alternative is never named and no condition is stated for choosing it. There is also no guidance on when a caller should call list_converters first to obtain a valid slug, or when to prefer get_conversion_status over waiting. Usage is implied rather than specified.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that results are scoped to 'the caller', which is meaningful behavior, but it says nothing about how rate-limit/credit values are represented or whether the data is live or cached. With an output schema present, return structure needn't be explained, so a 3 is appropriate.

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 with no filler; every word contributes (verb, scope, three returned data classes). Nothing to trim.

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 no-argument read tool with annotations covering safety and an output schema covering the return shape, the description contains everything needed to invoke it correctly. The only shortfall is the absence of explicit guidance on when to call it relative to the conversion flow.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The 'caller's' wording usefully signals implicit scoping from the auth context rather than a parameter.

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 ('Return') and concrete resources ('API credits, usage, and rate limit'), so an agent knows exactly what it gets back. It never mentions the conversion siblings, but the subject matter is so clearly disjoint (account usage vs. document conversion) that confusion is unlikely.

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?

Usage is implied by the payload: an agent should call this to check quota or rate limits before or after conversions. There is no explicit when-to-use statement, no mention of when it is unnecessary, and no reference to alternatives.

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?

Annotations already mark this as a read-only, open-world operation, so the safety profile is covered. The description adds one valuable behavioral fact — a completed job yields an absolute, temporary download URL — but does not disclose job states (pending/failed), whether URLs expire after a fixed period, or error behavior.

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 tight sentences with the core purpose front-loaded followed by the key output fact. 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?

An output schema exists, so return values need not be explained, and annotations cover the read-only nature. However, the description omits where job_id originates and any polling guidance, which are meaningful gaps for a status-check tool.

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 single parameter job_id has 0% schema description coverage, and the description does not explain where the job ID comes from (presumably returned by a conversion call) or its format. That leaves the only required input under-specified in both places.

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 ('check') and resource ('DOCX.now conversion job'), which clearly separates it from the sibling converters like list_converters and convert_image_url. It does not explicitly name alternatives, but the resource noun alone is enough to tell an agent what the tool targets.

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?

Usage is implied — you check a conversion job after starting one — but the description never says so, nor does it mention polling cadence or when to prefer another sibling. There are no explicit when-not conditions.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that the catalog is 'live' and that results are valid slugs, which is useful context about freshness of results, but says nothing about result volume, ordering, or pagination behavior beyond what the schema hints at.

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 sentence with the core action front-loaded and the example slugs providing concrete grounding. Nothing extraneous.

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?

With an output schema present and annotations covering the read-only/closed-world profile, the description does not need to explain return values, and the slug examples are a bonus. The remaining gap is the undocumented query parameters, which is a modest but real omission for a 2-param tool at 0% schema coverage.

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%, so the description carries the burden — yet 'limit' is never mentioned and 'search' is only vaguely gestured at through the word 'Search'. It does not explain matching semantics (substring vs slug-prefix), default page size of 50, or the 100 cap.

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 and resource ('Search the live DOCX.now converter catalog') and even previews the return shape with concrete slug examples (docx-to-pdf, pdf-to-docx). It implicitly separates itself from siblings like get_conversion_status and get_api_usage by being the discovery tool, but never names an alternative 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 intended use — finding valid converter slugs — is implied by the return-value examples, so an agent can infer it should call this before a conversion. There is no explicit statement of when to use it versus the sibling tools, nor any exclusion or prerequisite.

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