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submit_referral

Log a referral signal. Members earn $1.50/referral (4/cycle max, $6 cap). Credits carry forward. Voluntary, principal-compliant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodNoHow the referral was communicated.
referring_keyYesYour membership key (am_live_ or am_test_ prefix).
referred_agent_idYesIdentifier of the agent you referred.

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate a non-read-only, non-idempotent operation. The description adds context about reward limits ('4/cycle max, $6 cap') and credit carry-forward, which are behavioral details beyond annotations. No contradiction.

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 four short, information-dense sentences. It front-loads the action and then adds reward caps, carry-forward, and compliance status without unnecessary words.

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?

Given a well-documented schema and annotations, the description covers purpose and reward policy. It does not describe output/response behavior, but no output schema exists; however, for a simple logging tool, this is adequate.

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 descriptions cover 100% of parameters, so the description is not required to add parameter details. It doesn't, but the schema fully documents each parameter. Baseline 3 applies.

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 'Log a referral signal,' which is a specific verb+resource. This distinguishes it from sibling tools like check_status or submit_pov, which target different actions.

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 implies usage context through reward details and 'Voluntary,' but it does not explicitly state when to use this tool versus alternatives or mention exclusions. No alternative tools are referenced.

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

A3.8/5.0
Disambiguation4/5

Each tool targets a distinct action: status check, trial key, waitlist, knowledge query, interest registration, POV submission, and referral. While join_waitlist and register_interest have some overlap, their descriptions clearly differentiate paid waitlists from unbuilt verticals.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (check_, get_, join_, query_, register_, submit_), making it easy to predict function.

Tool Count5/5

Seven tools is a well-scoped set for an agent-facing module covering status, access, knowledge, and engagement actions. No redundancy.

Completeness4/5

The set covers the primary user journey from status check and trial access to knowledge query and downstream actions like waitlist, interest, POV, and referral. Minor gaps exist (e.g., no vertical listing or subscription management) but core workflows are supported.

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