lrn_relationship_query

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating safe reads. The description adds behavioral context by specifying it queries 'live NPAC porting data' rather than static LERG, which informs agents about data freshness and source. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the main purpose, and each sentence adds value. No redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description does not specify return format, but it clarifies data source (live NPAC) and enumerates query types. For a simple query tool with 2 parameters, this is sufficient to set agent expectations, though additional details on output structure would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters (query_type and value). The description lists example query types, which the schema already enumerates. It adds minimal extra meaning beyond the schema, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool queries relationships in the LSMS database, lists specific query types (phones_by_lrn, spid_by_lrn, etc.), and distinguishes from static LERG data by saying 'Queries live NPAC porting data (not static LERG reference data).' This effectively differentiates it from sibling tools like lerg_query.

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

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

The description implicitly guides usage by listing query types and noting the data source (live NPAC vs static LERG). However, it does not explicitly state when to use this tool versus alternatives like lrn_lookup, nor does it provide when-not-to-use scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.