aiworkhub_dashboard_model_settings_update

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

With no annotations, the description carries the full burden and does well: it discloses the write nature, that a model-settings lock is acquired, that expected_revision is verified, and that persistence is atomic. It stops short of stating auth/permission requirements or whether a toggle is reversible, which are the remaining gaps for a mutation tool.

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?

Front-loaded 'USER WRITE' marker, then a purpose sentence, then usage/alternatives, then concurrency behavior. Two dense sentences with no wasted text and correct ordering of decision-relevant information.

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?

Output schema exists, so return values are already covered; the description supplies the concurrency, locking, and alternative-tool context an agent needs before calling a write operation. Nothing essential is missing for correct invocation.

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 each parameter (including the model-under-adapter relationship and expected_revision fail-closed behavior) is already documented. The description reinforces the three-level switch concept (provider → adapter → model leaf) but adds little syntax or meaning beyond the schema, so the baseline 3 holds.

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 (update) plus resource (one provider, adapter, or model routing switch) and scope (active repository). The 'USER WRITE' prefix and the reference to 'model routing switch' clearly separate it from aiworkhub_dashboard_settings_update (repository feature flags) without needing the schema open.

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?

Explicitly names what it is for (enable/disable a provider, transport adapter, or model leaf) and gives alternatives: call aiworkhub_dashboard_settings first to read model_policy/revision, or use aiworkhub_dashboard_settings_update for feature flags. Prerequisite and sibling routing are both spelled out.

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