load_event_log

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

With no annotations, description discloses format inference, supported formats, key parameters for CSV/Parquet, return type, and that it never returns the log itself. Lacks side effects or error info but sufficient.

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?

Concise and well-structured: purpose first, then format details, then key parameters, then return value. No unnecessary 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?

Covers all aspects: what the tool does, format support, parameter roles, return structure (dict with log_id and summary including counts, preview, time range, top variants). Output schema exists but description adds sufficient 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?

Schema has 0% description coverage, but description fully compensates by explaining each parameter: path, format (inferred), *_key parameters as column mappings with defaults and purpose.

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?

Description clearly states 'Read an event log from disk and store it under a fresh log_id handle,' specifying the action and resource. It distinguishes from siblings which are mostly analysis or visualization tools.

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?

Describes when to use (loading event logs), format inference, and that subsequent tools retrieve by handle. No explicit alternatives but context implies other load tools for different formats like load_ocel.

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