Skip to main content
Glama

aya_validacao_aprovar_saida

Approve the validated output by setting the final approval flag, ensuring the workflow can proceed after successful validation.

Instructions

Selo final calculado. A LLM nao fornece aprovado=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The one claim — that the LLM does not provide aprovado=true — hints at the tool's role but never states what the tool does, returns, or mutates. A cryptic fragment is not an adequate behavioral contract.

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

Conciseness2/5

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

The description is short, but it is under-specified rather than concise — two cryptic sentence fragments that fail to state what the tool does. The brevity does not earn its place because the content is essentially uninformative.

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

Completeness1/5

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

Although the schema is trivial (0 params, no output schema), the description is completely inadequate: it never explains what the 'final seal' means, what action the tool performs, or where it fits in the validation flow. An agent cannot decide to call this tool correctly based on this definition.

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 0 parameters with 100% schema coverage, so there is nothing for the description to document and the baseline is 4. The mention of 'aprovado=true' is the only semantic hint and is not tied to any parameter, but no parameter information is required here.

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

Purpose1/5

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

The description ('Selo final calculado. A LLM nao fornece aprovado=true.') contains no verb-resource statement of what the tool does; it reads as an internal workflow note about a state, not an action. Despite the name suggesting an approve-exit validation step, an agent cannot determine the tool's function from this text.

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

Usage Guidelines1/5

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

There is no guidance on when to call this tool, no preconditions, and no mention of alternatives such as the sibling aya_validacao_gates. Among a large family of validation-related tools, the agent receives zero routing information.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/testesvibecodeing/AyA-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server