Botverse

Convert Uploaded Document

convert_file

Offload a document conversion to Botverse using an already-uploaded file. Workflow: (1) call get_upload_url to get a presigned upload form, (2) POST the file to that URL as multipart/form-data (all upload_fields first, then the file), (3) call convert_file with the object_key — Botverse handles the rest server-side. Returns a job_id immediately so you can continue with other tasks while conversion runs. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx, pdf, html, txt, md, rst, xlsx. Poll get_job_status until complete, then get_download_url. Flat fee $0.05 per file. If you are in a sandboxed environment where the get_upload_url PUT is blocked, do not use this tool — use convert_content (inline content under 500 KB) or convert_from_url (public URL) instead; no upload needed.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`object_key`	Yes	The object_key returned by get_upload_url.
`output_format`	Yes	Target format: docx \| html \| txt \| md \| rst \| pdf \| xlsx

Output Schema

TableJSON Schema

Name	Required	Description
`job_id`	Yes	Unique identifier for this job. Pass to get_job_status and get_download_url.
`status`	Yes	Initial job state — always queued or processing immediately after submission.
`estimated_seconds`	No	Rough estimated processing time in seconds. Actual time may vary.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedMay 25, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description discloses critical behavioral traits beyond the annotations: it returns a job_id immediately (async behavior), has a flat fee of $0.05 per file, supports specific input/output formats, and requires a multi-step upload workflow. Annotations only indicate non-read-only and non-destructive; description adds substantial context and does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but front-loaded with the primary purpose. While it includes a detailed workflow, every sentence carries necessary information (steps, async result, formats, cost, alternatives). It is longer than minimal but earns its length; still, it could be slightly more concise by merging some procedural details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool requiring a multi-step upload workflow, the description is exceptionally complete: it outlines prerequisites, the exact sequence of calls, the immediate return value, supported formats, cost, and fallback alternatives. It also covers the sandbox limitation. No critical context is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully documents both parameters (object_key and output_format) with descriptions and an enum. The description restates the output formats and mentions that object_key comes from get_upload_url, but does not add new semantic meaning beyond the schema. With 100% schema coverage, baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose clearly: 'Offload a document conversion to Botverse using an already-uploaded file.' It specifies the verb (convert), the resource (an uploaded file), and the context (document conversion). It also distinguishes from siblings by explaining the upload prerequisite and mentioning alternatives (convert_content, convert_from_url) for different scenarios.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use and when-not-to-use guidance: it spells out a three-step workflow, says to poll get_job_status and get_download_url, and explicitly warns 'If you are in a sandboxed environment where the get_upload_url PUT is blocked, do not use this tool' with named alternatives. This is exactly the kind of usage clarity expected.

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

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TDQS

A4.1/5.0

Disambiguation4/5

Each operation is split into clear source-specific variants (URL, uploaded file, inline content), and the descriptions go to great lengths to distinguish them. The only mild ambiguities are generic-sounding names like transcode_video versus transcode_from_url, and the similar get_job_status/get_workflow_status pair, but there is no true functional overlap.

Naming Consistency4/5

Most tools follow an imperative verb_noun pattern and use recurring suffixes like _from_url, _content, and _file, which creates a readable family structure. The pattern breaks slightly with uploaded-media variants named conform_media, transcode_video, and transcribe_media instead of a consistent _file or _uploaded suffix, and transcode_content is referenced in a description but missing from the actual tool list.

Tool Count4/5

17 tools is slightly above the ideal 3-15 range, but the server covers several related subdomains: document conversion, media transcode/transcribe/conform, job/workflow lifecycle, and wallet/billing. Given the need for URL, uploaded, and inline variants across multiple media types, the overall count is reasonable.

Completeness3/5

Core workflows are well covered: uploading, job submission, polling, and retrieving outputs all exist, and conversion has content/file/URL routes. However, get_upload_url explicitly tells agents to use transcode_content for inline media, but that tool does not exist, and there is no inline transcribe counterpart to convert_content, leaving a notable gap for sandboxed inline media jobs.

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