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wm_govern

Check whether an AI action is allowed under workspace policy without executing it. Unknown actions are denied by default, and sensitive actions can require human approval.

Instructions

Check whether an AI action is allowed by the workspace policy without performing it. Unknown actions are denied by default. Write actions can require a preview, and sensitive actions can require a named human approver. The decision is recorded in the hash-chained journal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathsNo
actionYesAction to check: read, write, execute, delete or network.
previewNo
approverNo
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does well by stating that the action is not performed, that unknown actions are denied by default, that write actions can require a preview, that sensitive actions can require an approver, and that the decision is recorded in a hash-chained journal. This provides meaningful behavioral context beyond the name and schema.

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 compact and front-loaded. The first sentence states the core purpose immediately, and the following two sentences add essential behavior without fluff or repetition of schema field names.

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?

The description explains governance semantics well but leaves important gaps for a tool with no output schema: it does not describe the shape of the result, what happens when preview or approver are actually needed, or how 'paths' factors into the decision. These missing details reduce an agent's ability to invoke the tool and interpret its response 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 description coverage is only 25%, so the description needs to compensate. It adds meaning to 'preview' and 'approver' implicitly through the write-action and sensitive-action sentences, but it never explains the 'paths' parameter, which is a notable gap. The 'action' parameter is covered by 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?

The description opens with a specific verb and resource: 'Check whether an AI action is allowed by the workspace policy'. It also clarifies that the tool does not perform the action, which clearly differentiates it from execution-type tools and from siblings like wm_audit, wm_explain, and wm_verify.

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 description gives context for when to use the tool: before an AI action, to check policy compliance. It also explains default behavior for unknown actions and special cases for write and sensitive actions. However, it does not explicitly state when NOT to use it or point to an alternative sibling tool for a given scenario.

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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