crehq_resolve_entity_affiliation

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fully lists the return fields (affiliation_status, canonical name, entity type, brand, operator, parent company, confidence, evidence, checked time) and explicitly states that independent, not_a_commercial_venue, and unresolved are valid outcomes, warning against inventing affiliations beyond the evidence. It also discloses a payment flow (purchase_url, intent_id, Pro key installation) and the need to reconnect, which is an important behavioral side effect.

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 appropriately sized for the tool's complexity. It is front-loaded with purpose and usage, then details parameters, return values, and special cases. Each sentence provides distinct information—no fluff—and the structure flows logically from what to when, how, and edge behaviors.

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 that there is no output schema and no annotations, the description is exceptionally complete. It covers the tool's purpose, appropriate usage, input criteria, full list of return fields, acceptable outcome statuses, and a specific paid-access workflow. This equips an agent to select and invoke the tool correctly, even without additional structured metadata.

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?

The input schema already provides descriptions for all 5 parameters (100% coverage), so the baseline is 3. The description adds meaningful semantic value by specifying that at least one of url, venue_name, or address is required (though the schema allows empty) and that additional identity hints improve disambiguation. This is crucial guidance not present in the schema.

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 clearly states the tool's function: resolving a public venue or business identity into its affiliation (chain, brand, operator, owner, or independent). It defines specific use cases (asking which chain a venue belongs to, who operates it, or if it's independent) and lists categories (hotels, restaurants, etc.), making it easy to distinguish from sibling tools like crehq_locations_search or crehq_company_get.

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 explicitly says 'Use this when the user asks which chain or brand a venue belongs to, who operates or owns a location, or whether a venue is independent,' providing clear when-to-use context. It also instructs to provide at least one of url, venue_name, or address and notes that additional hints improve disambiguation. However, it does not explicitly mention when not to use the tool or name alternative tools for other cases.

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