index_create_project_log_index

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

With no annotations provided, the description carries the full burden. It discloses idempotency (returns confirmation without modifying existing index), which is valuable behavioral context. It also lists the full set of fields/schema supported, giving the agent a clear picture of what gets created. Could add more about latency or side effects but is solid for a no-parameter setup tool.

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?

Well-structured with clear sections, front-loaded with the core purpose sentence, then supporting details and example prompts. The field list is a bit verbose but useful. The example prompts add practical value. Slightly long but every section earns its place.

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, idempotent setup tool, the description is quite complete. It covers what gets created (all fields incl. vector embedding), idempotency behavior, and example invocations. The output schema exists, so return values aren't needed. Minor gap: doesn't clarify preconditions like whether an Azure AI Search resource must already exist, but this is a well-covered setup operation.

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 0 parameters, so there is nothing to explain beyond what the schema shows. Schema coverage is 100% with an empty parameter list. The description zeroes in on what the tool accomplishes rather than parameters, which is appropriate for a parameterless operation.

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 states a specific verb+resource ('Create the project log search index in Azure AI Search') and lists the detailed schema fields it sets up. It clearly distinguishes from siblings like index_ingest_project_log (ingesting data) and search_vector_db (searching).

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?

Provides clear context on what the tool does and explicitly notes it's safe to call idempotently ('Safe to call if the index already exists'). Includes example prompts showing intended usage patterns. However, it doesn't explicitly state when NOT to use it versus alternatives (e.g., vs ingest for populating data).

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