Agent Module

submit_pov

Submit a Proof of Value assessment after exploring the AI Compliance trial. Includes quality scoring and subscription intent. Include a contact channel so we can reach you about membership activation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "trial_key": "<trial_key>",
      "confidence_score": "<confidence_score>"
    },
    "name": "submit_pov"
  }
}

Input Schema

Name	Required	Description
`review`	No	Free-text review (up to 1024 chars).
`contact`	No	How to reach you about membership or follow-up. String (email, webhook URL, agent card URL) or object { type, value, label }. Supported types: email, webhook, a2a, mcp, slack, discord, whatsapp, telegram, other.
`trial_key`	Yes	Your trial key (am_trial_ prefix).
`confidence_score`	Yes	Overall confidence in knowledge quality (0.0–1.0).
`modules_accessed`	No	List of module IDs accessed during trial.
`vertical_interest`	No	Verticals you are interested in.
`intent_to_subscribe`	No	Do you intend to subscribe after the trial?
`architecture_assessment`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedMar 23, 2026

TDQS

A3.9/5.0

Behavior3/5

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

Annotations are all false, offering no safety or side-effect hints. The description adds some behavioral context by noting that including a contact channel enables follow-up about membership activation, but it does not disclose persistence, idempotency, or side effects beyond the submission itself. This is minimal but non-contradictory.

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

Conciseness5/5

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

The description is concise—two sentences, front-loaded with the action, and no filler. Every sentence earns its place by conveying purpose and an actionable requirement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a submission tool with 8 parameters and no output schema, the description gives the essential purpose but leaves gaps. It does not clarify that 'contact' is optional despite being phrased as an instruction, nor does it mention other optional fields like modules_accessed or vertical_interest. It is adequate but not exhaustive.

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

Parameters3/5

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

Schema coverage is high (88%), so the description does not need to explain individual parameters. It adds minor value by tying 'quality scoring' to confidence_score and 'contact channel' to contact, but it does not introduce new meaning beyond what the schema already provides.

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

Purpose5/5

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

The description uses a specific verb ('Submit') and resource ('Proof of Value assessment'), clearly distinguishing this tool from siblings like check_status or join_waitlist. It also states the context ('after exploring the AI Compliance trial') and key components, making the purpose unmistakable.

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

Usage Guidelines4/5

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

The description provides a clear usage context: 'after exploring the AI Compliance trial.' It implies this is the post-trial submission tool, contrasting with pre-trial siblings like join_waitlist or register_interest. However, it does not explicitly name alternatives or exclusions, so it falls short of the strongest guidance.

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

All Agent Module tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.