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TetreesEX

Tetrees AI

Official
by TetreesEX

Submit AI Pack for Agent AVCP

submit_ai_pack_for_audition

Submit a completed AI pack for audition by moving it into the immutable Agent AVCP queue after readiness checks pass.

Instructions

Move a complete owner-bound draft into the immutable Agent AVCP queue after readiness passes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productIdYesTetrees AI Pack product id
confirmationYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.2.1

TDQS

A3.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It adds meaningful context by describing the queue as 'immutable' and requiring 'readiness' to pass, implying a consequential and irreversible state transition. It does not mention the confirmation constant or failure behavior, but the core side effect is disclosed.

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 front-loaded sentence with no filler. It communicates the action and key preconditions efficiently, though domain jargon like 'immutable Agent AVCP queue' reduces immediate clarity.

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 tool with no annotations, no output schema, and simple parameters, the description covers the readiness precondition and the immutable destination. It omits what happens if readiness has not passed, whether the submission can be withdrawn, and the role of the confirmation token, leaving some workflow details to inference.

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 only 50%: productId has a description, while confirmation only has a const value. The description adds context that productId refers to a complete owner-bound draft, but it does not explain the confirmation parameter. The const value 'SUBMIT_AGENT_PACK' is self-documenting, so invocation is still feasible.

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 ('Move') and names a clear resource ('complete owner-bound draft' into the 'Agent AVCP queue'), so the core action is understandable. It distinguishes itself from run/publish siblings by focusing on queue submission, though it does not explicitly name a sibling and 'Agent AVCP' jargon is unexplained.

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 phrase 'after readiness passes' gives an implied precondition and suggests a workflow with get_ai_pack_submission_readiness. However, it does not explicitly state when to use this tool versus quote_ai_pack_audition, run_ai_pack_audition, or publish_ai_pack, and no exclusions are provided.

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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