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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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reviewNoFree-text review (up to 1024 chars).
contactNoHow 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_keyYesYour trial key (am_trial_ prefix).
confidence_scoreYesOverall confidence in knowledge quality (0.0–1.0).
modules_accessedNoList of module IDs accessed during trial.
vertical_interestNoVerticals you are interested in.
intent_to_subscribeNoDo you intend to subscribe after the trial?
architecture_assessmentNo

TDQS

A4/5.0
Behavior3/5

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

Annotations already state readOnlyHint=false, destructiveHint=false, idempotentHint=false, indicating a mutating non-idempotent operation. The description adds that the submission includes quality scoring and subscription intent, and that a contact channel is needed for membership activation. It does not detail side effects like record creation or follow-up actions, but it adds some context beyond annotations.

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 two sentences, front-loaded with the core purpose, and includes only necessary guidance. Every sentence earns its place without redundancy.

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

Completeness4/5

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

With 8 parameters and nested objects, the description is brief but leverages high schema coverage (88%). It communicates the essential outcome (submit POV, quality scoring, subscription intent, contact requirement) and complements the schema well. Lacks explicit return-value behavior, but no output schema is defined, so this is acceptable.

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 description coverage is 88%, so the schema already documents most parameters. The description adds meaning by highlighting 'quality scoring' (confidence_score), 'subscription intent' (intent_to_subscribe), and 'contact channel' (contact), but does not provide syntax or format details beyond the schema. This is adequate for the high coverage.

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 clearly states a specific verb and resource: 'Submit a Proof of Value assessment.' It explicitly ties to the AI Compliance trial context and distinguishes from sibling tools like register_interest and submit_referral by specifying this is the POV submission step.

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 gives clear usage context: 'after exploring the AI Compliance trial.' It also provides an actionable guideline to 'Include a contact channel so we can reach you about membership activation.' However, it does not explicitly exclude alternative tools or state when not to use it, so it falls short of a 5.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool addresses a distinct action: operational status, trial key, waitlist, knowledge query, interest registration, proof-of-value, and referral. There is no overlap in purpose, making tool selection unambiguous.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (e.g., check_status, get_trial_key, query_knowledge). Even the two 'submit' verbs are distinguished by their objects, maintaining a clear and predictable convention.

Tool Count5/5

With 7 tools, the server is well-scoped for its purpose of managing user engagement (status, trials, waitlists, knowledge queries, interest, POV, referrals). Each tool earns its place without unnecessary bloat.

Completeness4/5

The tool set covers the core user journey from status checks and trial access to knowledge retrieval, POV submission, waitlist joining, and referrals. Minor gaps exist, such as a dedicated tool for listing all verticals, but check_status partially fulfills this via seat/count information.