aiworkhub_dashboard_settings

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

Goes well beyond the readOnlyHint annotation by stating it reads repository configuration files and status views 'without mutating durable state or starting background services' — a concrete behavioral guarantee about side effects that annotations alone do not 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?

Front-loads the READ-ONLY marker, then purpose, then routing guidance, then side-effect guarantees — every sentence carries information. Slightly dense in the final sentence, but no filler.

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?

An output schema exists, so return values need no explanation here. The description covers purpose, sequencing relative to the update tools, sibling exclusions, and side effects — nearly complete for a zero-parameter read tool, with only minor detail (e.g. what a 'revision number' looks like) left implicit.

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?

The tool takes no parameters, so there is nothing for the description to disambiguate and the baseline is 4. No parameter noise is introduced, which is correct here.

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 (return) and enumerates the exact configuration domains covered: repository feature switches, Source Graph policy, retention policy, and model routing policy. An agent can distinguish this settings-inspection tool from aiworkhub_dashboard_snapshot and the three settings_update siblings without opening any schema.

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 gives the when: inspect current settings and revision numbers before calling aiworkhub_dashboard_settings_update, aiworkhub_dashboard_model_settings_update, or aiworkhub_dashboard_source_graph_settings_update. It also names the exclusion and the correct alternative — 'For queue state or task counts use aiworkhub_dashboard_snapshot instead.'

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