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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. Beyond that, the description adds real behavioral context: the output is simulation-derived with no interpretation drift, per-chapter OEE/throughput are genuine reference values, deltas are computed rather than estimated, and results should be quoted verbatim — all of which materially shapes how an agent should present the response.

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 output contents are front-loaded, followed by usage examples and then the anti-fabrication constraint, which is a sensible order. The ALL-CAPS 'ANTI-FABRICATION' and 'Quote VERBATIM' phrasing is slightly heavy-handed, but every sentence carries operative information and nothing is redundant.

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?

With no output schema, the description carries the burden of describing returns, and it does list the compared fields plus the provenance of the numbers. What remains unstated is the response shape itself — how the two columns and the delta are surfaced — so it is strong but not fully complete.

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% and the schema descriptions already explain both enum parameters, including that bs1-leds is the canonical first-look comparison and shares plant data with bs1-ct. The description adds essentially no parameter-level meaning beyond what the schema states, so the baseline 3 applies.

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 names a specific verb and resource ("side-by-side comparison of two chapters") and enumerates the compared dimensions: tracks, topology, OEE, throughput, headline bottleneck. That clearly separates it from single-chapter reads like get_chapter_facts, though it never explicitly distinguishes itself from run_buffer_tradeoff or run_gain_loss, which are the closest analytical siblings.

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?

Three concrete example questions ('how does X compare to Y?', 'what's the difference between Constraint-Level and LEDS-Level on the same model?', 'what changes when we add buffers?') give an agent a clear trigger condition. It stops short of exclusions — notably it does not say to prefer run_buffer_tradeoff when the question is specifically about adding buffers, even though that phrasing appears in the examples.

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