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

Annotations only say readOnlyHint=false and destructiveHint=false, which the description extends meaningfully: it explains that nothing is deleted, that a deleted false claim returns with the next ingestion while a corrected one does not, and that corrections are stored with owner attribution and surfaced first by lab_wissen. That is exactly the behavioral context annotations cannot convey.

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?

Four tight sentences, each carrying distinct weight: trigger condition, timing rule, what gets stored, deletion semantics, and one authoring convention. No filler, well front-loaded with the primary instruction.

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?

Covers trigger, timing, persistence semantics, refusal behavior for unknown sources (carried by the schema for `quelle`), and the lab_wissen readback loop. For a mutation tool with no output schema, this is complete enough to call correctly on the first try.

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%, so all five properties are already documented in the schema. The description adds one operational hint — quote the user's own wording for `korrektur` — but the other parameters (quelle, thema, behauptung, url) get no additional narrative. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (record a correction) and resource (in the FilmOS knowledge layer), scoped to the trigger (when the user contradicts something you asserted from it). The sibling lab_wissen is named as the surface that reads this data back, so the tool's role in the knowledge loop is unambiguous.

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 timing rule ('the moment a contradiction is stated — not at the end of the session') and an explicit exclusion ('not instead of accepting the correction in your answer'). This is textbook when/when-not guidance tied to an observable condition.

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