Diyaliz Stabilite Skoru hesapla

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

With no annotations, the description carries the full burden and does substantial work: severity thresholds (19–28 stabil, 10–18 izle, <10 acil), independent red flags (K ≥ 6.5, albumin < 2.5), the per-parameter return contents (score, color, trend, clinician message), handling of missing parameters, and an explicit no-storage/PII prohibition. It stops short of stating determinism, validation-error behavior, or that it is a pure side-effect-free computation, which keeps it out of the top band.

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?

Six dense sentences with essentially no filler: purpose, scale, red flags, return contents, missing-data handling, and safety disclaimer each add information. It is delivered as one undifferentiated block, so thresholds and the return-value sentence are not as visually front-loaded as they could be.

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 12-parameter, nested-object tool with no output schema, the description covers output shape, alarm semantics, and partial-data behavior well enough to call it correctly. The remaining gap is input-importance prioritization and the relationship to dss_yontem, which an agent would need in order to decide between the two.

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 baseline is 3, and the description adds genuine meaning beyond the schema by tying concrete lab values to alarm behavior (K ≥ 6.5, albumin < 2.5) and by warning that patient identity must not be supplied even though the object schema accepts free-form values. It still does not clarify which of the 12 optional inputs actually move the score versus merely adding context (the schema hints Kt/V is 'bağlam için', but the description is silent).

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?

Names a specific verb and resource with a version marker: "Diyaliz Stabilite Skoru (DSS v2.0.0) hesaplar" for a hemodialysis patient. It immediately defines the output scale (0–28, higher = better) and the interpretation bands, so an agent knows exactly what the tool produces without consulting the schema.

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 eligible population is implied (hemodialysis patients) and the tool self-describes as clinical decision support, but there is no explicit when-to-use/when-not guidance and no mention of the sibling dss_yontem (methodology), so an agent must infer the routing between the two. Usage is implied rather than directed.

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