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delimit_agent_check

Verify whether an AI model has permission to perform an action under agent policy. Use as a per-action gate before executing sensitive operations.

Instructions

Check if a model is allowed to perform an action under agent policy (Pro).

When to use: as a per-action gate before executing sensitive operations from a non-orchestrator model — verify it has the required permission. When NOT to use: to set / inspect policies overall (use delimit_agent_policy) or for runtime governance evaluation (delimit_gov_evaluate).

Sibling contrast: delimit_agent_policy manages the policy; delimit_gov_evaluate is the runtime governance gate; this is a per-action permission check.

Side effects: read-only on the policy store. Calls ai.agent_policy.check_agent_permission.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesAI model name — "claude", "codex", "gemini", "cursor". Required.
actionYesAction to check (e.g. "ledger_write", "deploy"). Required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully carries the burden, stating side effects ('read-only on the policy store') and the underlying call. It clearly describes the behavior as a read-only permission check.

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 concise (around 100 words) with well-organized sections (purpose, when to use/not use, sibling contrast, side effects). Every sentence adds value without redundancy.

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?

Given the tool's simplicity (2 params, output schema exists), the description covers purpose, usage guidelines, behavioral transparency, and parameter context adequately. No obvious gaps remain for an agent to select and invoke this tool correctly.

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 coverage is 100% with descriptive parameter names and examples. The description does not add significant new information about parameters beyond what the schema provides, so baseline score of 3 is appropriate.

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 the tool checks if a model is allowed to perform an action under agent policy, using specific verbs and resource. It distinguishes from sibling tools (delimit_agent_policy, delimit_gov_evaluate) by noting it's a per-action permission check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit 'When to use' and 'When NOT to use' sections, including alternatives like delimit_agent_policy and delimit_gov_evaluate. The guidance is precise, recommending use before sensitive operations from non-orchestrator models.

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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