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get_policy_summary

Retrieve a high-level summary of your project's governance policy, including counts of allow/deny rules and approval requirements. Use it to understand active guardrails before attempting policy-restricted actions.

Instructions

[policy] Return a high-level summary of the project's .q-ring.json governance policy — counts of allow/deny rules for tools, key reads, exec commands, plus approval and rotation requirements. Use to orient an agent (or the user) on what guardrails are active before attempting policy-restricted actions; prefer check_policy for a precise per-action verdict. Read-only. Returns pretty-printed JSON; missing policy file returns an empty/default summary rather than an error so callers can branch on the counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoAbsolute path to the project root for project-scoped secrets and policy resolution. Defaults to the MCP server's current working directory when omitted.
Behavior5/5

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

Even with no annotations provided, the description discloses key behavioral traits: it is read-only, returns pretty-printed JSON, and handles a missing policy file by returning an empty/default summary instead of throwing an error. This gives callers confidence in side-effect-free operation and predictable failure behavior, going well beyond the 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 three sentences, each earning its place: purpose and content, usage guidance with alternative, and behavioral notes. It is front-loaded with the core purpose and contains no redundant or vague wording.

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 simple tool with one optional parameter and no output schema, the description covers all essential aspects: what it returns (counts and requirements), how to use it, safety (read-only), output format, and error behavior. It is complete enough for an agent to invoke correctly and interpret results.

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 100% for the single projectPath parameter, so the baseline is 3. The description does not add extra parameter-specific semantics beyond referencing the governance policy file, but it doesn't need to since the schema already explains the parameter's purpose and default behavior.

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 returns a high-level summary of the project's .q-ring.json governance policy, listing specific content such as counts of allow/deny rules, key reads, exec commands, and approval/rotation requirements. It distinguishes itself from the sibling check_policy by explicitly noting to prefer that tool for precise per-action verdicts.

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?

The description provides explicit when-to-use guidance: to orient an agent on active guardrails before attempting policy-restricted actions. It names the alternative tool (check_policy) and clarifies the division of labor, which is exactly the kind of usage guidance needed.

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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