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lurq

Read the dependency policy

policy
Read-only

The rules this account's selection policy enforces on which packages you may add: denied packages (with the reason), license allowlist, confidence, advisory, adoption, staleness and bundle-size floors. Read it once before choosing dependencies so you pick an allowed package first; evaluate already enforces it. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered; the description's trailing 'Read-only' largely restates it. It does add genuine context beyond the annotations: the policy is account-scoped and is advisory for selection while 'evaluate' performs actual enforcement. It does not mention caching, freshness, or what an empty result means.

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?

Front-loaded with the core statement of what the policy governs, followed by a dense but necessary enumeration of the policy dimensions and then the usage cue. The single multi-clause sentence is economical, though the middle list is packed tightly enough that it reads as a run-on.

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?

With no output schema, the description carries the return-value burden and does so by naming the fields an agent will get back (denials with reasons, allowlist, assorted floors). Combined with the usage cue, an agent has everything needed to decide whether and when to call it.

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?

The tool takes zero parameters, which is the baseline-4 case: there is no argument surface an agent could get wrong. The description correctly implies a parameterless read of account-wide policy rather than a per-package query.

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 (read) and resource (the account's selection policy), then enumerates exactly what the policy contains: denied packages with reasons, license allowlist, and confidence/advisory/adoption/staleness/bundle-size floors. It also distinguishes itself from the sibling 'evaluate', which enforces the same policy, so an agent can tell the two apart without opening anything.

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?

Gives an explicit when: read it once before choosing dependencies so the first pick is already allowed. It also gives the implicit when-not by noting that 'evaluate already enforces it', so re-reading purely to gate a single evaluation is unnecessary. Both the trigger and the alternative are named.

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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