rir_as_relationships

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

Annotations cover safety profile (readOnly, idempotent, non-destructive). Description adds value by disclosing the inference methodology (BGP-path-based algorithm), classification taxonomy (upstream/downstream/settlement-free), and external data source (CAIDA AS-Rank API).

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?

Docstring format (Args/Returns) is slightly verbose but efficiently structured. Classification bullets front-load key value propositions. Every section earns its place, particularly parameter documentation which fills schema gaps.

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?

Comprehensive for a data-fetch tool: covers source API, inference methodology, classification categories, parameter details, and return format. Well-supported by annotations covering safety; no significant gaps despite zero schema description coverage.

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 has 0% description coverage but description fully compensates via Args section: documents 'asn' with format examples ('AS13335' or '13335'), and 'response_format' with allowed values and default. Explains semantics beyond raw schema types.

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?

Specific verb 'Fetch' + resource 'AS relationship data' + explicit scope (CAIDA AS-Rank API). Explicitly distinguishes from sibling/alternative RIPE Stat asn-neighbours tool by contrasting accuracy levels and classification methods.

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?

Provides clear comparative context: explains that unlike RIPE Stat (which gives left/right/uncertain), this uses BGP-path-based inference for higher accuracy, implicitly guiding selection when accurate classification is needed. Lacks explicit 'when not to use' constraints.

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