get_us_liquidity

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

Beyond the readOnly/idempotent annotations, the description discloses material behavior: total_available only sums same-date items, restricted cash is never included in the total, missing items are reported as not_reported rather than 0, and official_runway becomes unavailable when restricted/maturity data is absent. This gives an agent accurate expectations about edge cases and calculation semantics.

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 information-dense but well-organized: a short lede, concrete example questions, then bullet points covering the most critical behavioral rules and exclusions. Every sentence adds distinct value, and the structure makes the key caveats easy to parse.

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 the tool has an output schema and only one parameter, the description covers all essential contextual aspects: data source, item composition, same-date summation rule, missing-data semantics, relation to runway calculation, and pointer to the sibling tool for burn. Nothing critical seems missing for an agent to invoke it correctly.

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 input schema only defines ticker as a string with no description, so the description must carry the semantic burden. It does so by specifying 'US ticker' and providing examples like RIVN and CRSP. This is adequate for a single parameter, though it could add detail on ticker format expectations or delisting/non-US edge cases.

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 identifies the tool as a US liquidity ledger built from SEC XBRL data, and enumerates the specific questions it answers around available cash, restricted cash, short-term investments, revolver, debt maturities, and post-report financing. It also distinguishes itself from a simple cash line in a financial summary, so an agent can tell what this tool uniquely provides.

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 gives concrete use-case examples and states an important boundary: this tool does not compute runway months, and the burn denominator should come from get_us_financial_statement. It names the relevant sibling and clarifies what the tool is not for, though it stops short of a comprehensive when-to-use vs. when-not-to-use matrix for all sibling alternatives.

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