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

Annotations already declare read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds real behavioral detail an agent cannot get from structured fields: credit_price silently defaults to the latest public median (an external-data dependency despite openWorldHint=false), and the applicable percentage falls back to the statutory floor unless overridden.

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?

Two dense sentences with no filler, and the computed outputs are front-loaded. The listing of inputs is somewhat compressed into one long clause, but nothing is wasted.

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?

No output schema exists, so the description carries the burden of indicating return values, which it does by naming annual credits, 10-year credits, and equity. It omits units and the assumed credit period convention, but the inputs and defaults an agent needs are 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 coverage is 100%, so the baseline is 3. The description earns above that by surfacing the default for credit_price and the floor-vs-applicable_percentage precedence rule, which the schema states only obliquely ('when the floor does not apply').

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 precisely what is computed: annual and 10-year housing credits and equity from eligible basis, applicable fraction, credit type, boost and credit price. This is clearly distinct from siblings like calculate_max_rent or get_equity_pricing. It is a noun-phrase description rather than a verb-led one, which slightly weakens the imperative signal.

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?

There is no explicit when-to-use or when-not-to-use guidance and no reference to alternative tools, even though get_equity_pricing and get_applicable_percentages are close neighbors an agent might confuse it with. The closing note about sharing math with the lihtc.loans estimator is provenance, not routing guidance.

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