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Sats4AI - Bitcoin-Powered AI Tools

send_email

Destructive

Reach anyone with an email address — useful when your task requires formal communication, sending reports, or contacting someone outside chat. No SMTP server, no domain verification needed. Plain text, max 10,000 chars body, 200 chars subject. 200 sats. Pay with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='send_email'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesRecipient email address
bodyYesEmail body text (plain text, max 10,000 characters)
replyToNoOptional reply-to email address
subjectYesEmail subject (max 200 characters)
paymentIdYesValid payment ID (must be paid)

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare destructiveHint=true, consistent with sending email. The description adds behavioral details: plain text, size limits, cost (200 sats), payment requirement, and no SMTP/verification. It does not cover delivery guarantees or errors, but annotations reduce the burden.

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 relatively concise with front-loaded purpose. Each sentence adds information, though it could be better structured (e.g., separating requirements from capabilities).

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

Completeness3/5

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

The description covers purpose, constraints, cost, and prerequisites, but it does not mention return values or potential errors. Since there is no output schema, the description should explain what the tool returns (e.g., success status). This gap reduces completeness.

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 coverage is 100%, so baseline is 3. The description adds value by explaining how to obtain the paymentId (via create_payment) and reiterating constraints like max lengths. It also mentions plain text, which is in the schema but confirmed.

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 sends email ('Reach anyone with an email address') and specifies use cases like formal communication, reports, or contacting outside chat. It distinguishes from sibling tools by focusing on email, not SMS or fax.

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 provides context for when to use the tool (formal communication, reports, external contacts) and mentions prerequisites (requires create_payment). However, it does not explicitly state when to avoid using it 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.