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Glama

record_answer

Store a user-provided answer to a form question so future job applications can reuse it automatically.

Instructions

Store a user-supplied answer so future applications reuse it.

Call this immediately after the user answers something, including the exact wording of the question as the form asked it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
answerYes
contextNo
questionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 behavioral disclosure. It states 'store' implying a mutation, but does not describe side effects, idempotency, whether it overwrites previous answers, or the return value. An agent cannot anticipate the tool's behavior beyond the basic action.

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

Conciseness4/5

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

The description is concise at two sentences, with the core purpose front-loaded and the usage guideline in the second sentence. There is no wasted text, making it efficient and easy to parse.

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?

Despite having an output schema (not shown here), the description omits important context: what happens after storing, potential errors, and any prerequisites. Given the absence of annotations and the 0% schema coverage, the description is not complete enough for an agent to fully understand the tool's behavior and edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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 mentions including 'exact wording of the question' which gives some guidance for the 'question' parameter, but it does not explain the 'answer' or 'context' parameters at all. The context parameter has a default but its purpose is unexplained. This is insufficient compensation for the schema gap.

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

Purpose4/5

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

The description clearly states the tool stores a user-supplied answer for future reuse, with a specific verb and resource. It also gives a concrete trigger ('immediately after the user answers something'). However, it does not explicitly differentiate from sibling tools like record_vision_fallback, which could also record user-provided data, so it's not a full 5.

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

Usage Guidelines3/5

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

The description provides a clear condition for when to call the tool (immediately after the user answers), which is helpful. But it does not mention any alternatives or when not to use it, leaving the agent to infer that this is the primary recording tool. This is adequate but not explicit about routing.

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