get_entity

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

No annotations are provided, so the description bears full burden. It discloses that aliases resolve automatically, which is a behavioral detail, but fails to state whether the operation is read-only, its latency, or any side effects. Given the absence of annotations, the description is adequate but not comprehensive.

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 short sentences. The first sentence succinctly states the purpose and output content. The second provides the required parameter condition and an example. No unnecessary words; front-loaded with essential information.

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 the complexity (dossier with cross-referenced data) and no output schema, the description mentions articles, aliases, and sentiment as output components. However, it does not detail the full response structure or pagination. For a single-entity fetch, this is adequate but could be more specific.

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 good descriptions for both parameters (slug and ticker) with examples. The description adds the important constraint that exactly one must be provided, which is not enforced by the schema, and gives concrete alias resolution examples (CZ -> changpeng-zhao), adding clarity beyond 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 fetches a 'canonical BCA entity dossier' with specific content (cross-referenced articles, aliases, sentiment) and lists entity types (chain, project, person, organization, ticker). This differentiates it from siblings like get_price or get_sentiment that likely return only single data points.

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 specifies that exactly one of 'slug' or 'ticker' is required, which is a key usage constraint. However, it does not compare this tool to alternatives like list_entities or get_sentiment, leaving the agent to infer when to use this specific dossier retrieval.

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