Destila la esencia irreductible de un concepto (su principio de fondo). Úsalo para obtener el núcleo conceptual de algo. input=concepto. [x402: 0.01 USDC on Base, pay-per-use]
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | concepto/cosa a destilar |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral transparency burden. It discloses the pay-per-use cost ('0.01 USDC on Base, pay-per-use'), which is useful operational context. However, it does not describe output format, side effects, or any limitations beyond pricing.
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 front-loaded, with the core purpose stated first. The usage instruction and pricing note are useful. The 'input=concepto' fragment is slightly redundant with the schema, but it does not significantly bloat the description.
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?
For a simple, single-parameter conceptual tool, the description adequately covers purpose, how to call it, and cost. It does not specify the output shape, but no output schema exists and the tool's output is naturally a text explanation of a concept's essence.
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%, and the description adds 'input=concepto,' which only restates the schema's 'concepto/cosa a destilar.' Since the schema already defines the parameter well, the description adds limited additional semantic value.
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 clearly states a specific verb and resource: 'Destila la esencia irreductible de un concepto (su principio de fondo).' This conveys what the tool does and its outcome. However, it does not explicitly differentiate it from siblings like summarize, explain, or interpret, which could overlap conceptually.
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?
The description gives clear guidance on when to use the tool: 'Úsalo para obtener el núcleo conceptual de algo.' This is enough context for the intended use case. It does not state when not to use it or name alternative tools, but the usage intent is reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.
Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.
160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.
The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.