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delimit_agent_policy

Set or view per-model governance permissions for ledger, memory, evidence, deploy, and secrets. Use access levels or boolean flags to control AI model operations.

Instructions

Set or view per-model governance permissions.

When to use: to inspect or modify the access policy that gates each AI model's operations on the ledger, memory, evidence, deploy, and secrets. When NOT to use: for runtime governance evaluation (use delimit_gov_evaluate) or session policy (delimit_project_config).

Sibling contrast: delimit_gov_evaluate evaluates one action; this configures the per-model policy that those evaluations use.

Side effects: providing any of ledger/memory/deploy/evidence/ secrets/custom_constraints writes via ai.agent_policy.set_agent_policy. Empty/no-changes is read-only.

Access levels for ledger/memory/evidence: "read-only", "read-write", "none". Boolean flags for deploy/secrets: "true" or "false".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoAI model name — "claude", "codex", "gemini", "cursor". Empty = list all.
ledgerNoLedger access level.
memoryNoMemory access level.
deployNoAllow deploys ("true"/"false").
evidenceNoEvidence access level.
secretsNoAllow secret access ("true"/"false").
custom_constraintsNoComma-separated constraints, e.g. "no-deploy,no-publish".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Given no annotations, the description carries full burden. It discloses side effects (writes via ai.agent_policy.set_agent_policy, empty/no-changes is read-only) and explains access level values. However, it does not mention rate limits, auth requirements, or output format, but for a config tool this is adequate.

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 well-structured with clear sections (purpose, when to use, when not to use, sibling contrast, side effects, parameter details). It is front-loaded with the main purpose and concise without wasted 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?

Covers purpose, usage, side effects, and parameter semantics. With an output schema present, return values need not be detailed. The description adequately addresses the tool's complexity and provides sufficient context for an agent 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 baseline is 3. The description adds value by grouping parameters (ledger/memory/evidence as access levels with 'read-only', 'read-write', 'none'; deploy/secrets as boolean flags; custom_constraints as comma-separated) and clarifying allowed values beyond the schema descriptions.

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 'Set or view per-model governance permissions' with a specific verb and resource. It distinguishes itself from sibling tools like delimit_gov_evaluate and delimit_project_config by explaining their different purposes.

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?

Explicitly states when to use (inspect or modify per-model policy) and when not to use (runtime evaluation or session policy), with specific alternative tool names (delimit_gov_evaluate, delimit_project_config).

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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