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

Annotations already declare readOnlyHint=true and openWorldHint=false, and an output schema exists, so the safety and return-shape burdens are carried elsewhere. The description's remaining contribution is the content inventory and the downstream chaining hint; it says nothing about pagination, cost, or behavior when the disease id is unknown, so it adds moderate rather than rich context.

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?

Two compact, front-loaded sentences: content first, next action second. No filler, though the all-caps labels and dense comma list make it slightly harder to scan than plain prose.

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 an output schema, full parameter documentation, and read-only annotations, the description only needs to establish scope and sequencing, which it does. The one gap is discovery: it never points to list_lab_diseases for finding a valid id or to a sibling for multi-disease comparison.

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 100% and the disease enum list plus the samples parameter (0-25, examples per track) are fully documented in the schema, so baseline 3 applies. The description adds one meaningful link — that the same id is reused as the `disease` argument to next_results_gap_trial — but never explains what `samples` controls.

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?

States a specific verb (read) and resource (one disease bench) and enumerates exactly what the payload contains: cure definition, research tracks with trial counts, outcome ladder, program status, reference papers, readiness gates, results-gap queue link. It does not, however, differentiate itself from plausible siblings like get_disease_dossier, get_scoreboard, or list_ladders, so an agent must still infer which one to open.

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?

"NEXT: next_results_gap_trial with disease set to this id, then submit_results_gap" gives an explicit workflow handoff and parameter binding, which is strong sequencing guidance. It stops short of when-not-to-use or naming an alternative (e.g., compare_diseases for multi-disease views, list_lab_diseases for discovery), so it is clear context without exclusions.

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