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Onboard agents to governance

onboard_agents
Idempotent

Bulk-onboard agent identities to the governed fleet (Agent Governance). Accepts plain ids or {agent_id} descriptors in agents, A2A 1.0 Agent Cards in agent_cards (name/url/provider/version/protocolVersion), or MCP client descriptors, under an optional cohort + shared auto-suspend policy. Idempotent. Requires the agent_governance licence + a manage:agents grant (or a first-party super-admin). Agents also self-onboard on first token/call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentsNoAgent ids or descriptors ({agent_id, display?, cohort?})
cohortNoOptional shared cohort (provider/model/deployment group)
agent_cardsNoA2A 1.0 Agent Cards ({name, url, provider, version, protocolVersion, ...})
auto_suspend_thresholdNoOptional 0..1 auto-suspend deviation threshold for the cohort policy

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare idempotency and non-destructiveness, so 'Idempotent' is partly redundant, but the description adds real behavioral context: a licence prerequisite and a manage:agents grant (or first-party super-admin). It still doesn't describe the response or what happens to already-onboarded agents beyond the idempotency claim.

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?

Three dense sentences that are front-loaded with the core action, followed by input forms, then prerequisites. Every clause carries information, though the parenthetical field lists make it slightly heavy to scan.

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?

For a four-param, no-required, mutation-style tool with no output schema, the description covers input forms, idempotency, licensing, and the self-onboarding fallback. Return behavior is unspecified, but with no output schema declared and a bulk upsert shape, an agent has enough to invoke it correctly.

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 coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not: it clarifies `agents` takes either plain ids or {agent_id} descriptors and reveals that MCP client descriptors are also accepted for a loosely-typed array, plus the A2A Card fields and the cohort auto-suspend policy. This goes beyond restating the schema.

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?

States a specific verb and resource — 'Bulk-onboard agent identities to the governed fleet (Agent Governance)' — and scopes it as a bulk operation. An agent can distinguish it from siblings like run_ai_governance_audit or discover_shadow_ai without opening any schema.

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?

Explains the accepted input shapes and that onboarding is optional because 'Agents also self-onboard on first token/call,' which implicitly tells the agent when this tool is unnecessary. It never names an alternative tool or an explicit when-not-to-call condition, so it stops 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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