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

Annotations only declare readOnlyHint=true, so the description adds meaningful behavioral context: output components (trend, percentile, top_drivers), update cadence ('monthly since 2005'), normalization basis, and source lineage (BLS JOLTS). No contradiction with annotations; the description enriches the read-only profile with return-value detail.

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 two sentences, front-loading the core definition before listing use cases and update frequency. Every sentence earns its place; no redundant or vague wording. The 'Updates: monthly' fragment is informative and compact.

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 read-only tool with one optional parameter, the description is complete: it states the output bundle (score, trend, percentile, top_drivers, lineage), usage triggers, and update cycle. No output schema exists, but the listed return components give the agent a clear expectation of the response shape.

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 schema provides 100% coverage for the only parameter (`days`), including optionality, range (1-1825), meaning, and tier behavior. The description adds no parameter information, which is acceptable because the schema already fully documents it. Baseline 3 applies.

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 clearly states a specific verb ('Returns') and resource: a 0-100 US labor market tightness score with normalization details. It ties directly to the title and distinguishes the tool by naming the precise metric construction (BLS JOLTS job openings per unemployed worker, normalized 2020 trough to 2022 peak).

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 explicitly enumerates when to call it: 'when the user asks about labor market tightness, hiring difficulty, worker shortages, job openings vs unemployment, or wage pressure' and connects to business use cases like salary-band uplifts. It lacks when-not-to-use or named alternatives, but the positive guidance is strong.

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