conformance_alignments

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

With no annotations provided, the description fully discloses behavioral traits: it is alignment-based (vs. token replay), can be slow, supports multi_processing (with Windows spawn restrictions), and emits progress events to keep requests alive. This covers safety (read-only) and performance characteristics comprehensively.

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 (4 sentences) and front-loaded: purpose first, then trade-offs, then parameter caveats, then behavior. Every sentence adds value with no redundancy.

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 complex analysis tool with 3 parameters and an output schema, the description covers key aspects: purpose, performance trade-offs, platform restrictions, and timeout handling. It lacks explicit output description, but the presence of an output schema mitigates this. Sibling tools like 'conformance_token_replay' provide alternative context, but the description is largely self-sufficient.

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 description coverage is 0%, meaning the description must compensate by explaining parameters. However, it only elaborates on 'multi_processing' (its caveats) and does not explain 'log_id' or 'petri_id' beyond their implied role as identifiers. This leaves half of the parameters semantically under-described for an AI agent.

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 performs an 'Alignment-based conformance check,' which is a specific verb-resource combination. It distinguishes itself from the sibling tool 'conformance_token_replay' by noting it is more accurate but slower, effectively differentiating in purpose.

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 explicitly provides guidance on when to use this tool versus alternatives: 'More accurate than token replay but slower — can take minutes on large logs.' It also mentions the multi_processing option with platform-specific caveats and progress events for timeout handling, offering clear context for usage.

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