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

Annotations already establish the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds genuine behavioral substance by spelling out the rules the tool applies: the pre-January 29, 2023 exemption and which credits lack it, the 1 MW aggregation logic, and the ITC/PTC wage-continuation periods. It stops short of describing the answer format or how it behaves when dates are unknown or omitted.

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 content is substantive rather than padding, and the core purpose is front-loaded in the opening clause. But the entire description is a single run-on sentence of nested parentheticals (~150 words) that is hard to parse; it would benefit substantially from being split into scannable 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?

For a 7-parameter determination tool with no output schema, the description covers the decision logic comprehensively across credits, dates, work type, technology, and size thresholds. Its main gap is that it never describes what the response looks like, which matters more given there is no output schema to fall back on.

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% with four enums, so the baseline is 3. The description goes beyond the schema by tying parameter values to outcomes: which credits carry the construction-date exception, that apprenticeship applies to construction only while prevailing wages continue 5 years for the ITC and 10 for the PTC, and the 10/12.5/15% apprentice-percentage options. That interpretive linkage adds real meaning even though much of it echoes schema text.

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 states a specific verb and outcome: it says whether a project must meet prevailing wage and apprenticeship requirements to claim the increased (5x) credit. It is clearly the applicability gate among the PWA siblings, but it never names or contrasts itself with check_prevailing_wage, check_apprentice_hours, or pwa_overview, so sibling differentiation is left implicit.

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?

Usage is only implied: an agent can infer this is the gating check to run before computing wage or apprentice-hour requirements. There is no explicit 'use this when' trigger, no when-not condition, and no routing to the alternative sibling tools that handle hours, ratios, or good-faith requests.

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