kettenerklaerung_erklaeren

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

With no annotations provided, the description carries the full burden and delivers: it discloses the non-mutating guarantee ('Never changes the stored ketten_hash; the break stays visible, this only records who/when/why next to it'), the error-rejection behavior, the dry-by-default network behavior ('dry by default, no network without an explicit anker_kwargs override'), and the side-effect timing ('that backlog only ever changes at this moment'). This is exemplary behavioral disclosure for a tool with zero annotation coverage.

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?

The description is a single dense paragraph, but every clause earns its place: purpose, rejection conditions, non-mutation guarantee, anchoring behavior, and return-value nuance. Core purpose is front-loaded before operational details. It is longer than ideal but not bloated; minor structural improvement via separate sentences would be possible without adding content.

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 7-parameter tool with no annotations and no output schema, the description covers an unusually large surface: error behavior, side-effect profile, optional anchor flow, and the return field for the anchor case. The only notable gap is the return format when anker is not set -- the agent never learns what a successful explanation record looks like. The reference to 'anker_kwargs override' without that parameter appearing in the schema is also slightly opaque, though it reads as an environment-level override.

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 baseline is 3. The description adds genuine meaning beyond the schema: it clarifies access_log_id must reference a broken row (tying to the fabrication-rejection behavior) and substantially enriches the anker parameter by explaining anchor construction via ankerverfahren.py, the dry default, and the anker_rueckstand return behavior. The actor/model/session params correctly need no extra elaboration.

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?

The description names a specific verb ('Explain'), a precise resource ('broken audit-chain link (access_log.ketten_hash)'), and a concrete triggering scenario ('sanctioned rewrite of an already-logged row -- e.g. a migration that corrected a field'). This is far more specific than the tool name alone and leaves no ambiguity about what the tool is for, while being clearly distinct from the knowledge_/project_/annahme_ sibling families.

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 description gives explicit when-to-use context (broken chain caused by a sanctioned rewrite) and explicit rejection conditions ('Rejects with an error if access_log_id has no break (gespeichert==erwartet) or does not exist -- an explanation for a healthy row would itself be a fabrication'). It does not name an alternative tool, but the domain is unique among the siblings, so the guidance is functionally complete. A 5 would require naming alternatives.

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