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, but it only describes the input-to-output mapping. It does not disclose whether answering advances or mutates checker state, whether repeated calls are safe, or whether the call is read-only.
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 packs purpose, key parameter meaning, and the two possible result types with no filler. It is front-loaded and easy to scan.
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?
With no output schema, the description should explain the shape of the returned question or verdict and how to distinguish the two outcomes. It also does not say where the question id comes from, which an agent needs to chain calls correctly.
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 coverage is 0%, so the description must add meaning. It does clarify that 'question' is actually a question id and that 'choice' is the index of the selected option, which goes beyond the bare 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 clear input (question id + choice index) and an unambiguous output (next question or final verdict). It identifies the tool's role in the checker flow, though it does not explicitly contrast it with 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?
Usage is implied: call it when the user has answered a checker question and the next step is needed. It offers no explicit when-to-use or when-not-to-use guidance and does not mention alternatives such as checker_start or checker_tree.
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 checker_start, checker_answer, and checker_tree tools are closely related, but their roles are clearly distinguished: start gives the first question, answer traverses the guide, and tree provides the full structure for end-to-end reasoning. The enquiry tools are also distinct, though checker_start and checker_tree could be confused by an agent looking for the initial question.
Names mostly follow a clear domain-prefix pattern: checker_* for the decision guide and enquiry_* for enquiry metadata. submit_enquiry is a minor deviation since it uses verb_noun instead of the enquiry_ prefix, but the overall naming is readable and predictable.
Six tools is well-scoped for this server's purpose: three tools cover the towing capacity decision guide and three cover the enquiry submission flow. Each tool has a clear role with no redundant extras or overwhelming surface area.
The tool set fully covers the two core workflows: navigating and reasoning through the decision guide (start, answer, tree) and submitting a consent-based enquiry (describe, fields, submit). The two-step submission with confirmation token is handled within submit_enquiry, so there are no obvious dead ends or missing operations.