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Sats4AI - Bitcoin-Powered AI Tools

convert_file

Convert files between 200+ formats: documents (PDF, DOCX, XLSX), images (PNG, JPG, WEBP, SVG), audio (MP3, WAV, FLAC), video (MP4, AVI, MOV). Industrial-grade conversion engine — preserves formatting and quality. Returns download URL. 100 sats. Pay per request with Bitcoin Lightning — no API key, no account, no subscription needed. Requires create_payment with toolName='convert_file'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileUrlNoPublic URL to the file (provide this OR fileBase64)
paymentIdYesValid payment ID (must be paid)
fileBase64NoBase64-encoded file (provide this OR fileUrl)
extensionToYesTarget format without dot (e.g., 'pdf', 'docx')
extensionFromYesSource format without dot (e.g., 'pdf', 'docx')

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses key behavioral traits: requires payment (100 sats), returns a download URL, preserves formatting and quality. Without annotations, it carries the burden and does so adequately, though it could mention rate limits or file size constraints.

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 efficient and front-loaded with the core purpose, then lists format categories, quality, return type, and payment model. Every sentence serves a purpose, though it could be slightly more concise.

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?

Given the tool has 5 parameters, no output schema, and no annotations, the description provides sufficient contextual completeness: it explains the payment flow, the need for 'create_payment', and the expected output (download URL). The agent can use this to correctly invoke the tool.

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?

With 100% schema coverage, baseline is 3. The description adds context about the conversion process and payment requirement but does not elaborate on parameter details beyond what the schema already provides.

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 the tool converts files between 200+ formats, listing categories like documents, images, audio, and video. The verb 'convert' and resource 'files between 200+ formats' make the purpose specific and distinct from sibling tools like 'convert_html_to_pdf'.

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

Usage Guidelines4/5

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

The description explains the pay-per-request model with Bitcoin Lightning and explicitly mentions the prerequisite of calling 'create_payment' with toolName='convert_file'. However, it does not provide explicit when-not-to-use guidance or compare to alternatives.

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

Most tools have distinct purposes, but there is some overlap, especially among call tools (ai_call, place_call, open_voice_bridge) and image generation/editing tools (generate_image, edit_image, animate_image). Descriptions help differentiate, but an agent might still select the wrong one.

Naming Consistency4/5

The vast majority of tools follow a verb_noun pattern (e.g., generate_image, send_sms). A few exceptions exist (await_result, check_job_status, epub_to_audiobook) but the overall pattern is strong and predictable.

Tool Count3/5

With 50 tools, the server is very extensive. While each tool earns its place given the broad scope of AI services, the count feels high and could overwhelm agents, making selection less efficient.

Completeness5/5

The tool surface is remarkably comprehensive, covering generation, editing, conversion, communication, async management, payments, and error handling. There are no obvious gaps for the stated Bitcoin-powered AI toolkit purpose.