opensearch_list_indices

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

No annotations are provided, but the description adds valuable behavioral context: the tool returns specific fields (doc count, store size, health), sorting behavior, and the potential for a 403 error with an alternative. However, it does not explicitly state if the operation is read-only or mention other constraints like rate limits, so one point off.

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?

Three sentences efficiently cover the fallback, return data, and usage hint. No fluff or redundancy; every sentence serves a purpose.

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 zero parameters and an existing output schema, the description provides complete context: return structure, sorting, error handling, and a concrete use case. There is no missing information.

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?

There are zero parameters and schema coverage is 100%, so the baseline is 4. The description does not need to add parameter semantics, but it does add usage context 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 returns all indices sorted by name with doc count, store size, and health. It also explains the use case of finding exact index name before querying and describes the date-sharded naming pattern, distinguishing it from sibling tools like opensearch_search or opensearch_cluster_health.

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?

Explicitly provides a fallback alternative (opensearch_list_index_patterns) for lower privilege requirements, and explains when to use the tool (before querying for exact index name). This gives clear guidance on when to use this tool vs. alternatives.

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