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

With no annotations, the description carries the full burden. It discloses the critical behavioral trait that numbers are canonical reference values from real dys-cli runs, mandates verbatim quoting and forbids rounding/estimating, and clarifies that all eight chapters return verified numbers. This gives the agent strong ground truth expectations beyond what the schema provides.

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 front-loaded with the purpose and includes essential usage/anti-fabrication notes. It could be slightly more concise, but each sentence earns its place, especially the anti-fabrication instruction, which is critical for correct use.

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 low complexity (one parameter, no output schema), the description is quite complete: it explains what will be returned, emphasizes data provenance, and advises about follow-ups. It lacks information on return format/units, but the metrics are named, and the tool's simplicity does not require much more.

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 coverage is 100%, so the schema already fully describes the 'chapter' parameter with enum values and formatting details. The description adds only generic context ('selected chapter') and does not deepen parameter semantics beyond the schema, so baseline 3 is appropriate.

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 action ('bottleneck analysis') on a specific resource ('selected chapter') and lists concrete output metrics (availability, downtime split, throughput, OEE). It distinguishes from sibling tools by emphasizing 'Single Run' and per-chapter focus, making its purpose unmistakable.

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?

It clearly indicates when to use: for single-chapter bottleneck analysis, and explicitly says to re-call this tool for follow-ups about the same chapter. However, it does not mention when not to use it (e.g., for cross-chapter comparison) or name alternative tools, so no explicit exclusions/alternatives.

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