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

With no annotations provided, the description carries the full burden of behavioral disclosure. It excellently discloses a non-obvious trait: 'The monthly panel is MID-BACKFILL, so a months_back longer than the loaded window returns an explicit warning listing the lookbacks that ARE available — never a silently shortened comparison.' This is significant behavioral context beyond what a typical description offers.

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 exactly two sentences. The first uses an em-dash list to pack the purpose, output fields, and sorting options efficiently. The second sentence adds a critical warning about backfill behavior. Every word earns its place, and the information is front-loaded with the tool's role.

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 no output schema and no annotations, the description compensates well by enumerating the output columns (ticker, company, headcount, changes, rates, salary) and the backfill warning. It would be more complete if it also clarified the semantics of limit and min_headcount, but the core screening behavior and edge case handling are fully covered.

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 description coverage is 0%, so the description must compensate. It implicitly explains 'months_back' via 'N months earlier' and 'order' via 'fastest-growing or fastest-shrinking', but it does not address 'limit' or 'min_headcount'. The schema provides defaults and constraints but no semantic descriptions, leaving those two parameters partially unexplained.

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 opens with 'CROSS-SECTIONAL HIRING SCREEN' and clearly states it 'rank[s] listed employers by headcount growth', enumerating exact output fields and sort options. This is a specific verb+resource combination that distinguishes it from sibling tools like tengu_v3_workforce_momentum by emphasizing the 'screen' cross-sectional nature.

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 phrase 'who is actually staffing up (or quietly shrinking) months before it reaches a filing' clearly articulates the use case — early signal screening via workforce data. It provides clear context for when to use the tool but does not explicitly name alternatives or exclusions, so it stops short of a 5.

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