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get_trial_key

Get a free trial key for instant, OpenAI-compatible LLM inference without registration. Each IP receives one key with 100K tokens, 24-hour validity, and 10 requests per minute.

Instructions

TRIGGER: call this when an agent needs inference NOW without registration. Issues a free gc- key: 100K tokens, 24h TTL, 10 req/min, OpenAI-compatible. One key per IP (idempotent — same IP always gets same key back). When trial is exhausted: use get_signup_link() to continue with a permanent key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Without annotations, the description fully discloses behavioral traits: idempotency, rate limit, token limit, TTL, and that it's free. No contradictions or omissions.

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?

The description is extremely concise, with every sentence adding value. It is front-loaded with the trigger condition and contains no fluff.

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 no parameters and an existing output schema, the description covers the tool's purpose, constraints, and follow-up action comprehensively.

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?

The tool has zero parameters, and the description provides all necessary context. Baseline 4 for 0 params 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 clearly states the tool issues a free trial key for inference without registration, distinguishing it from siblings like get_signup_link(). It provides specific details: 100K tokens, 24h TTL, 10 req/min, OpenAI-compatible, and idempotent per IP.

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 explicitly says 'TRIGGER: call this when an agent needs inference NOW without registration' and advises to use get_signup_link() when the trial is exhausted, providing clear when-to-use and when-not-to-use guidance.

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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