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

Goes well beyond the annotations (readOnlyHint=false, destructiveHint=false): it discloses the async execution model (background, HTTP 202, poll via lab_get_job until done|failed), the return payload fields (passt, sicherheit, abweichungen, begruendung / error), the 16-image cap, and the scope limits (judges identity, not style/light/pose/props/micro-details). This is exactly the operational context an agent needs.

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?

Dense but front-loaded: purpose first, then scope exclusions, then cost, then async mechanics and prerequisites. Roughly five clauses, all carrying load; it is on the edge of long but 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 return-value burden and does so fully (job_id + poll pattern + result fields). Prerequisite, limits, and scope are all covered, so an agent has everything needed to invoke and follow up correctly.

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 documents all three parameters (baseline 3). The description adds genuinely new meaning: 'Up to 16 images per call, all completed images of this project' clarifies the expected content and scope of image_ids beyond the schema's per-field note.

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 ('Check whether...') and resource ('still images of a project show the SAME character as its character sheet'), and explicitly bounds what is compared (the sheet's detail and fullbody views). It is clearly distinguishable from siblings like lab_continuity_check or lab_abgleich because it names the reference artifact and the identity attributes judged.

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?

Gives a clear timing/context cue ('before paid clips are made from them') and names a prerequisite ('The sheet needs a reference image (lab_generate_character_reference)'). It does not explicitly say when NOT to use it or name a competing tool, so it falls short of a 5.

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