ecosystem_index_update

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

With no annotations, the description carries full burden. It details the pipeline steps, the verification of DataSource and ScanProfile, and the effect of dry_run=True preventing writes. It also references a bug fix related to dry_run. However, it does not explicitly state that setting dry_run=False persists changes to multiple database tables, nor does it mention potential side effects like alert triggering. Still, the level of detail is high.

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 moderately concise, with a clear first line summarizing the purpose. However, it includes internal details like a specific bug fix reference (BUG #6/#8) and test function name, which may be extraneous for an AI agent. The structure is front-loaded but could be more streamlined.

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 an output schema exists (not shown but present), the description covers the tool's input and behavior thoroughly. It explains the trigger, verification, pipeline steps, and dry_run implications. Return values are not described, but the output schema likely handles that. The description is complete for the tool's complexity.

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 coverage is 100%, providing a baseline of 3. The description adds meaningful context: it explains that dry_run=True (default) simulates the scan and returns a preview, while dry_run=False persists updates. This clarifies the parameter's impact beyond the schema's short description, making the parameter semantics richer.

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 triggers an ecosystem index update, specifying the pipeline steps from scanner to diff. It maps to a specific POST endpoint and includes verification steps, making the purpose unambiguous. While there are many ecosystem siblings, this tool is distinct in its focus on index updates, and the description differentiates by describing the full pipeline.

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 does not provide any guidance on when to use this tool versus alternatives like ecosystem_scan or ecosystem_refresh. It explains the dry_run behavior but fails to mention prerequisites or contexts where other tools would be more appropriate. The lack of comparative usage context is a significant gap.

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