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

With no annotations provided, the description carries the behavioral transparency burden. It discloses that the tool compresses input, produces a fewer-token version, and has a pay-per-use cost of 0.001 USDC on Base. But it does not describe potential quality trade-offs, whether meaning can be lost for very short prompts, or what exactly happens in edge cases, so there is still a meaningful gap.

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

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

The description is short and well-structured, front-loading the core purpose and expected savings, then giving the usage directive, then parameter note, then the fee note. Every sentence earns its place without unnecessary jargon.

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

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

Given the simplicity of the tool (one required string parameter, no nested objects, no output schema), the description provides enough to invoke the tool correctly: the input is a prompt, the output is a compressed version, and the cost is explicit. The missing output schema is not fatal because the description explains the return shape. It slightly falls short by not clarifying input limits or language handling.

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

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

Schema description coverage is 100%, since the sole `input` parameter is described as 'Texto/prompt a comprimir'. The description merely restates the same meaning ('input=text to compress') without adding syntax, expected format, or edge-case guidance, so the description adds little beyond the schema.

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

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

The description states a specific action ('Compress a prompt'), a clear resource ('prompt'), and the expected outcome ('return version with fewer tokens'). It distinguishes itself from sibling tools like count-tokens (which measures tokens) and summarize (which produces a human summary) by focusing on lossless token reduction.

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

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

It explicitly tells the agent when to use the tool: 'Use it BEFORE sending prompts to any LLM to cut token cost without losing meaning.' This is actionable and context-rich. However, it does not name alternative approaches or explain when not to use it, leaving some room for ambiguity.

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