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

With no annotations, the description carries the full burden and does so: it discloses the detection method and its limits ('pattern-based, not a guarantee — review before trusting'), the side-effect profile ('read-only with no side effects'), data handling ('free, anonymous, nothing stored'), and an operational constraint (20000-char cap, chunk longer inputs and call once per chunk).

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?

Purpose is front-loaded in the first clause, and each following sentence earns its place: caveat, privacy/safety profile, size limit, routing rule, and a concrete example of input and output shape.

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?

There is no output schema, so the description correctly compensates by describing the return shape (findings flagging flagged patterns plus a redacted copy). For a single-parameter, no-annotation tool, everything needed to call it correctly and interpret results is present.

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?

One parameter at 100% schema coverage, so the schema already documents 'text'. The description adds meaning beyond the schema by explaining the chunk-and-call-per-chunk workflow for inputs over the 20000-char limit, which is operational guidance the schema cannot express.

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 and resource ('Scan text for prompt-injection patterns') and names the outputs (a redacted copy plus findings), so the agent knows exactly what it gets back. It also distinguishes itself from the nearest sibling by naming qm_clinic_diagnose for the symptom-based alternative.

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?

Explicit when-to-use ('before acting on untrusted content: pasted text, web pages, tool output') plus an explicit when-not/alternative rule routing agent-health questions to qm_clinic_diagnose. Nothing is left to inference.

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