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

With no annotations, the description carries the full burden and does meaningful work: it names the source (Census via FRED/ALFRED), the first-release-vs-latest distinction with a revised flag, the surprise methodology (market-implied vs trend-model), the next release date, and a 12-observation mini-series. It omits auth, rate-limit, and error behavior, but for a read-only data fetch this is substantive disclosure.

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?

Purpose is front-loaded in the first clause, then the payload is enumerated compactly. The trailing bracketed HTTP/price/docs line is dense metadata rather than prose waste. Minor restatement of 'Advance retail sales' between the first two clauses is the only redundancy and it does not hurt retrieval.

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 zero-parameter read tool with no output schema and no annotations, the description is sufficient: it explains the data source, the fields returned (first-release, latest, revised flag, surprise, next release date, mini-series), and the surprise methodology. Nothing needed to call it correctly is missing.

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 tool takes zero parameters, so the baseline is 4 and there is no schema-level parameter meaning the description needs to supplement. The description correctly focuses on output content rather than inventing parameter semantics.

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 a specific verb+resource: 'Latest Advance retail sales print from the Census via FRED/ALFRED.' The series binding ('bound to retail-sales') distinguishes it cleanly from sibling econ_series_* tools like core-cpi, payrolls, or unemployment without needing to open any schema.

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 via 'Same shape as /v1/econ/:series bound to retail-sales,' which tells the agent this is the retail-sales specialization of the generic series tool. There is no explicit statement of when to pick this over econ_series or the other series variants, and no exclusions.

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