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convergeqa

convergeqa-mcp

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by convergeqa

convergeqa_iterate_start

Initiate a private, authenticated iterative review of text with multiple AI models, optional instructions, and reference material.

Instructions

Start a private authenticated Iterate agent review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYes
promptNoSynthetic or user-approved text to review. Not returned.
base_urlNoConvergeQA base URL.https://convergeqa.net
templateNoGeneral
model_tierYesRequired for agent review starts.
api_key_envNoUppercase environment variable name containing a ConvergeQA Developer API key.CONVERGEQA_API_KEY
prompt_fileNoLocal file path containing text to review. Not returned.
extra_promptNo
document_nameNoAgent Review
max_spend_usdNoOptional advisory spend cap for this service-account request.
system_promptNo
credential_kindNoauto
idempotency_keyNo
synthesis_modelNo
reference_materialNo
redact_private_urlsNo
additional_instructionsNo
service_account_key_envNoUppercase environment variable name containing the ConvergeQA service-account key.CONVERGEQA_SERVICE_ACCOUNT_KEY
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It states 'private authenticated' but does not elaborate on authentication mechanism (e.g., API key via environment variable). It fails to mention whether the start is asynchronous, what the response contains, or any side effects like costs or resource consumption.

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

Conciseness3/5

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

The description is a single concise sentence, which is front-loaded and easy to read. However, given the tool's complexity (18 parameters, many siblings), this brevity sacrifices necessary detail. It is not overly long, but it is under-informative.

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?

The tool has 18 parameters, no output schema, and many siblings. The description provides almost no context about the tool's purpose within the broader workflow, how to set up authentication, what 'Iterate agent review' entails, or what the agent should expect after starting. It is severely incomplete.

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 coverage is only 39%, yet the description adds no parameter explanations. It repeats nothing about 'models', 'prompt', 'credential_kind', etc. The description does not compensate for the low coverage, leaving agents to infer parameter usage from the schema alone.

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 specifies the verb 'Start' and the resource 'Iterate agent review', with qualifiers 'private authenticated'. This clearly distinguishes it from sibling critique tools. However, it does not explain what 'Iterate' means versus 'Critique', leaving some ambiguity.

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 on when to use this tool versus alternatives like convergeqa_critique_start or other iterate tools. No mention of prerequisites, conditions, or scenarios. The description provides no usage context.

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

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