discover_log_skeleton

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

No annotations are provided, so the description must fully disclose behavioral traits. It does not mention whether the tool is read-only, destructive, requires authentication, or any side effects. The description focuses on output but omits operational behavior.

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 with three sentences. It front-loads the main purpose and uses a code block for the parameter. No unnecessary details, though the code block is informal.

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, the description does not need to detail return values. It adequately explains the tool's function and key parameter, but lacks context on input prerequisites or log format requirements.

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 compensates partially by explaining noise_threshold (range [0,1] and pruning purpose). However, log_id is not described, leaving a gap. The added parameter info is useful but incomplete.

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 it discovers a log skeleton with six constraint types. It is a specific verb+resource and distinguishes itself from siblings like discover_petri_net or discover_declare by focusing on behavioral constraints per activity pair.

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 mentions it is 'useful as a declarative complement to Petri-net / process-tree discovery,' providing some context but no explicit when-to-use or when-not-to-use guidance. It lacks alternatives or exclusions.

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