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destilar-structured-json

destilar specialized for structured json [x402: 0.01 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYespipeline input

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

C2.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It does mention pay-per-use and the cost on Base, which is a useful operational detail, but it entirely omits what the tool does to the input, what the output looks like, whether it has side effects, or what limitations exist. The behavioral disclosure is minimal and insufficient.

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

Conciseness3/5

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

The description is a single short sentence and is front-loaded with the purpose phrase, with the pricing information appended. There is no wasted wording, but the main clause is a near-verbatim restatement of the tool name, so it is under-specified rather than elegantly concise. The pricing note is useful and earns its place, but the rest does not.

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

Completeness2/5

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

For an agent choosing among many destilar and JSON-related siblings, this description is incomplete. It lacks the expected input format, the output structure, and any indication of when this variant is preferable. The single parameter and no output schema increase the need for rich description, yet the description only offers a name restatement and a payment detail.

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?

Schema description coverage is 100% for the single 'input' parameter, so the baseline is 3. The description adds no parameter-level detail beyond what the schema already states, and both the description and schema leave the expected format of 'pipeline input' vague (e.g., raw text, JSON string, object). It does not actively mislead, but it also does not enrich the schema.

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

Purpose2/5

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

The description 'destilar specialized for structured json' is essentially a restatement of the tool name with no action verb. It does not state what the tool does with structured JSON—whether it extracts, generates, transforms, or validates it. It only distinguishes itself from siblings like destilar-tables or destilar-batch by naming 'structured json', but still fails to define the actual function.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool instead of destilar, destilar-batch, ocr-structured-json, extract-json, or json-fix. There are no usage conditions, no exclusions, and no mention of input type or intended use case. The only additional context is the pricing note, which does not help with tool selection.

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

C2.6/5.0
Disambiguation1/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.

Completeness3/5

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.

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