Botverse

Convert Document from URL

convert_from_url

Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL — direct download links and share links from Dropbox, Google Drive, OneDrive (personal or business), SharePoint, and Box all auto-resolve to the file. If you already have the content as a string, use convert_content instead — no upload step needed. Runs entirely server-side, so it works in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) — the right route there for files too large for convert_content's 4 MB inline limit. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_output_content (inline, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`source_url`	Yes	Public HTTPS URL of the source document.
`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.

TDQS

A4.9/5.0

Behavior5/5

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

Annotations provide only basic safety hints. The description adds critical behavioral context: asynchronous processing (returns job_id), polling workflow, server-side execution, auto-resolution of share links, and a flat fee. No contradiction with annotations.

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

Conciseness5/5

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

Though lengthy, every sentence provides distinct value: purpose, usage, alternatives, formats, workflow, cost. Structured logically and front-loaded with the core action.

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?

Complex asynchronous tool with cost and sandbox constraints. Description covers return value, next steps, polling, retrieval methods, and limitations (4 MB inline limit for alternative). Output schema exists and is not redundant with description.

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

Parameters4/5

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

Schema already has 100% coverage with descriptions for both parameters. The description adds value by explaining auto-resolution of share links for source_url and the xlsx output meaning (tables extracted), which goes beyond the schema.

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 clearly states what the tool does with a specific verb ('offload a document conversion') and resource (document from a URL). It distinguishes from siblings by explicitly directing string content to convert_content and mentioning supported formats.

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?

Explicit when-to-use guidance: 'Use this when the source document is at a public URL.' It also mentions alternatives (convert_content) and context (sandboxed environments, large files). No exclusions left ambiguous.

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

A4/5.0

Disambiguation4/5

Tools are largely distinguishable by their action and input source (content/file/url), but the multiple convert_* and transcode/transcribe variants overlap in purpose, and get_job_status vs get_workflow_status could cause confusion. Descriptions are thorough enough to guide selection, but the boundaries between similar actions are not always crisp.

Naming Consistency4/5

All names use snake_case with a verb-noun pattern (get_, convert_, transcode_, transcribe_, submit_, cancel_), which is consistent. However, the variant naming is not perfectly parallel: convert_content/file/from_url use a source suffix, whereas transcode_video vs transcode_from_url and transcribe_media vs transcribe_from_url mix output type and source, creating minor inconsistency.

Tool Count4/5

At 15 tools, the server is at the upper end of a well-scoped set. Each tool supports a distinct input/output route or workflow function, but the count is slightly heavy due to multiple variants of similar operations. It remains appropriate for the breadth of conversion, transcoding, transcription, workflow, and wallet features.

Completeness3/5

The core job lifecycle (submit, poll, retrieve output) is well covered, and workflows have submit/status/cancel. However, get_upload_url references a transcode_content tool that does not exist in the toolset, and there is no way to cancel a single job (only full workflows). This leaves gaps for inline media transcoding in sandboxed environments and granular job control.

Resources

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