checker_answerGiven a question id and the chosen option (its choice index), return the next question or the final verdict.
| Name | Required | Description | Default |
|---|---|---|---|
| choice | Yes | ||
| question | Yes |
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?
With no annotations, the description carries the full burden of behavioral disclosure. It explains the input-output relationship but does not disclose error behavior, side effects, or the branching condition between 'next question' and 'final verdict'. This leaves the agent guessing about important runtime behavior.
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?
A single sentence with no filler. The conditional input is front-loaded and the output is stated directly, making it easy to parse quickly.
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?
Although the tool has only two simple parameters, it appears to be part of a multi-step flow with siblings like checker_start and checker_tree. The description does not clarify how to obtain a valid question id or when a 'final verdict' is returned, and there is no output schema to compensate.
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 0%, so the description must compensate. It adds useful meaning by clarifying that 'question' is an id and 'choice' is the chosen option's index, but it omits details about id format or how choices are enumerated.
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 clear action: given a question id and a choice index, it returns the next question or final verdict. This makes the tool's core purpose understandable, though it does not explicitly distinguish it from siblings like checker_start or checker_tree.
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 phrase 'Given a question id and the chosen option' implies when the tool should be used, but it does not explain prerequisites, such as obtaining the question id from checker_start, nor does it specify when to prefer this over sibling tools. Usage context is only implicit.
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.
Each tool has a clearly distinct purpose: checker_start initiates the flow, checker_answer advances it, and checker_tree provides the full static tree. The three enquiry tools are equally distinct: describe explains the process, fields defines the schema, and submit_enquiry performs the actual submission.
The naming uses domain prefixes (checker_*, enquiry_*) which helps, but the word ordering is inconsistent: checker_answer and enquiry_describe are noun_verb, checker_tree and enquiry_fields are noun_noun, while submit_enquiry is verb_noun. This mixed convention makes the set slightly less predictable.
Six tools is a well-scoped count for this server. It covers two small workflows without unnecessary duplication or overwhelming the agent.
The checker workflow is fully covered with start, step-by-step answering, and full tree access. The enquiry workflow is also complete: overview, field schema, and a two-step submission process with validation and confirmation.