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request_agent_training_pair_admission

Request admission for an agent training pair by specifying project, revision, and idempotency key, then confirm with a receipt to bind the admission.

Instructions

Explicitly request governed-training admission for an installed action.

First call with confirmation false to receive a request-bound confirmation_receipt. Set confirm_admission_request=true and return that exact receipt only after the user explicitly asks to make this admission request. The receipt binds installation, revision, optional project, and a digest of the idempotency key; a bare boolean is insufficient. Confirmation is required even though the current production gateway always returns structured HTTP 503 schema lightbulb.training_pair_admission.v1 and performs zero writes. This guard remains in place so a future admission implementation cannot become consequential silently.

There is currently no production admission authority, scheduler, launcher, or persisted/installable worker surface. The six blockers returned by preflight_agent_training_pair are authoritative.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNo
revision_idYes
idempotency_keyYes
installation_idYes
confirmation_receiptNo
confirm_admission_requestNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Addedv0.1.1

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and does so exceptionally. It discloses that the current gateway performs zero writes, always returns HTTP 503, requires confirmation regardless, binds the receipt to specific fields, and that no production admission infrastructure exists. This is outstanding behavioral disclosure.

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 dense but every sentence earns its place: purpose, two-step procedure, receipt contract, current production reality, and authoritative preflight reference. It is front-loaded with the core action and contains no filler.

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

Completeness5/5

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

For a governed-admission tool with no annotations, the description comprehensively covers the call sequence, confirmation requirements, current no-op behavior, and how to interpret preflight blockers. An output schema exists, so restating return values is unnecessary.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It meaningfully explains confirmation_receipt, confirm_admission_request, the idempotency_key digest binding, and the installation/revision/project binding. installation_id and revision_id remain somewhat self-evident, but the confirmation-related parameters are well clarified.

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 opens with a specific verb and resource: 'Explicitly request governed-training admission for an installed action.' It clearly identifies the tool's operation and references the related preflight_agent_training_pair, helping distinguish it from sibling tools like get_agent_training_pair_status.

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 explicit procedural guidance: call once with confirmation false to get a confirmation_receipt, then set confirm_admission_request=true only after user confirmation. It also names preflight_agent_training_pair as authoritative for blockers, giving strong contextual routing, though it does not enumerate all when-not-to-use conditions.

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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