filter_attribute_values

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

Without annotations, the description carries the full burden. It clearly details the different behaviors for level and retain parameters, and even warns about a deprecation issue with PM4Py. However, it does not specify whether the tool modifies the log in place or returns a new filtered log, which is relevant for understanding side effects.

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 concise (four sentences) with the core purpose in the first sentence. Subsequent sentences efficiently explain key parameters and a practical nuance (deprecation warning). No redundant or extraneous content.

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 the presence of an output schema (so return values need not be described) and the moderate complexity (5 parameters, 3 required), the description covers the essential filtering behavior and parameter effects. It could be slightly more complete by elaborating on the attribute and values parameters or providing an example.

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?

With 0% schema description coverage, the description must compensate. It explains level and retain well, but provides minimal explanation for required parameters like attribute and values (only implicit from 'filter by attribute values'). Log_id is left unexplained. Thus, it adds some value but not enough to fully cover all parameters.

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 filters a log by attribute values at event or case level, and the name 'filter_attribute_values' aligns with this. It effectively distinguishes the filtering functionality from sibling tools like filter_variants or filter_time_range by specifying the attribute-based criterion.

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 explains when to use each level (event vs. case) and the effect of retain (keep vs. drop). However, it does not explicitly guide when to use this tool over other filtering siblings (e.g., filter_time_range for temporal filters), nor does it mention prerequisites or limitations.

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