cos_details

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

Annotations provide no safety profile (all hints false), so the description carries the burden. It states 'Get' and 'Returns: str: JSON with full record,' signaling a retrieval operation, but it does not explicitly address whether the call is read-only, what happens on missing IDs, or any error behavior.

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 compact with a clear one-line purpose and separate Args/Returns sections. Every sentence earns its place, with no unnecessary filler.

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?

For a simple 2-parameter details fetch with an output schema, the description covers the arguments and return format sufficiently. It could add an example or note about error cases, but the current level is adequate for selecting and invoking the tool.

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 description adds real meaning beyond the bare schema by explaining pattern_id as 'Row ID (or task_id string for task_outcomes)' and source as 'observations, learned_patterns, or task_outcomes.' The possible type mismatch with the schema's integer pattern_id is a minor concern, but the special case is still useful.

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 opens with 'Get full details of a pattern, observation, or task outcome,' using a specific verb and specifying the resources. It is clear about the operation, though it does not explicitly differentiate it from sibling query tools like cos_search or cos_graph_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 implies usage: given a row ID and a source table, retrieve the full record. It does not state when to choose this tool over alternatives, nor does it mention exclusions or prerequisites, so the guidance remains implicit.

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