edgegate_list_eval_packs

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

With no annotations, the description discloses important behavioral details: its return schema (id, name, case count, balance), the fact that it is a read-only listing, and the global scope without workspace_id. It does not mention pagination or ordering, but for a simple list with zero parameters, this is sufficient and more transparent than typical.

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, front-loaded with the verb and resource, and every clause adds value: what is listed, what is returned, how to consume the result, and a key scoping note. No wasted words.

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 zero-parameter list tool with no output schema, the description fully covers the purpose, return contents, and follow-up action. It is complete enough for an agent to select and invoke the tool correctly without additional context.

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 tool has zero parameters and the schema is empty, so the baseline is 4. The description goes further by explicitly stating 'No workspace_id needed' and explaining why (global library), which preemptively clarifies a common expectation and adds meaning beyond the empty 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 lists 'bundled behavioral eval-set starter packs' and specifies the returned fields (id, name, case count, balance). It distinguishes this from related tools like edgegate_list_eval_sets by emphasizing these are customer-clonable starter packs, not user-created eval sets.

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 provides explicit use context: it is for browsing packs that can be cloned, and it directs the agent to edgegate_create_eval_set(clone_from=<id>) as the follow-up action. It also notes 'No workspace_id needed' since the library is global. However, it does not explicitly state when not to use it (e.g., do not use for listing existing eval sets), so it misses the 'when-not' element for a perfect score.

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