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Glama

Assess Submission

assess_submission

Determine if a job application qualifies for automatic connector submission by assessing MFA, captcha, identity verification, and consent requirements.

Instructions

Decide whether an application can use an authorized automatic connector.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_urlYes
mfa_requiredNo
captcha_presentNo
ambiguous_questionsNo
identity_verification_requiredNo
consent_or_declaration_requiredNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It does not state whether the tool fetches or inspects source_url, whether it only evaluates the provided boolean flags, or what side effects or checks occur. The term 'authorized' also implies some permission model that is never explained.

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 a single sentence with no filler, and the core purpose is front-loaded. However, brevity is achieved by omitting needed context, so it is concise but not optimally structured for guidance.

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 a six-parameter decision tool with no annotations, this description is incomplete: it does not explain how the inputs combine into a decision, when to call the tool, or what the decision is based on. The output schema reduces the need for return-value text, but the input semantics and workflow context remain undefined.

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

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description mentions none of the six parameters. The agent is left to infer the meaning of source_url, mfa_required, captcha_present, ambiguous_questions, identity_verification_required, and consent_or_declaration_required solely from their names, which is insufficient for a decision tool.

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 uses a specific verb ('Decide') and names the assessed resource ('an application'/'authorized automatic connector'), so the core function is identifiable. However, it does not differentiate from sibling tools like submission_hard_stops or verify_snapshot, and the phrase 'authorized automatic connector' is jargon that is not explained.

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?

No guidance is provided about when to use this tool versus alternatives such as submission_hard_stops, verify_snapshot, or track_application. The description only states what the tool does, without prerequisites, exclusions, or workflow context.

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