get_labor_actions

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

No annotations are provided, and the description does not disclose any behavioral traits such as data freshness, rate limits, authentication requirements, or read-only safety. While the tool appears to be a simple query, the absence of transparency about potential costs or side effects leaves gaps for an AI agent.

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?

Description is extremely concise (three sentences) with the main action and coverage stated upfront. Every sentence adds value: first defines purpose, second details content, third identifies users. No redundant or vague statements.

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?

Given zero parameters, no output schema, and no annotations, the description fully explains what the tool returns (labor events with specific fields) and its intended use case. An AI agent has sufficient information to understand when to invoke this tool for labor disruption analysis.

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?

Tool has zero parameters, so the baseline is 4. The description adds no parameter information, but none is needed since schema coverage is 100% and there are no inputs to document.

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?

Description clearly states the tool retrieves labor actions from news intelligence, explicitly listing covered types (strikes, lockouts, slowdowns, contract negotiations, protests) and specific fields (union, employer, location, etc.). It distinguishes from sibling tools by focusing on labor-specific disruptions, contrasting with broader tools like get_disaster_events or get_action_signals.

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?

Description provides clear context by identifying target users (logistics planners, procurement teams) and use case (assessing labor disruption risk at ports and manufacturing facilities). However, it lacks explicit guidance on when not to use this tool or how it compares to siblings beyond the implied domain specificity.

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