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

Annotations already declare read-only, idempotent, non-destructive, and open-world hints, so the description's added value comes from disclosing default returns, the meaning of the reference date, and ONS geography codes. It also notes the data source and license. There is no contradiction with annotations, and the description reasonably complements them with operational details.

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 three sentences plus a source line, all front-loaded with the core purpose. Each sentence contributes meaningfully (scope, granularity, default behavior, parameter usage), and there is no filler or redundancy.

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 presence of an output schema and full parameter documentation, the description covers the essential call semantics: default values, geography codes, and what the data represents. It does not explicitly address year selection or whether results are time-series, but given the simple 3-parameter schema and output schema, this is a minor gap rather than a blocker.

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 100%, but the description goes beyond the schema by enumerating the actual ONS geography codes (K02000001=UK, etc.) and explaining that the age parameter supports single-year-of-age breakdowns. This adds practical selection guidance that the schema alone does not fully provide.

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 ('Retrieve'), resource ('mid-year population estimates'), and geographic scope (UK, England, Wales, local authorities), clearly distinguishing it from sibling tools like ons.stats.gdp or abs.demographics.population. It also specifies the reference date (30 June) and granularity (area, age group, sex), leaving no ambiguity about what the tool does.

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 clear context: when UK population estimates are needed, this is the tool. It also explains the default behavior (England and Wales, all ages/sexes) and how to select geography via codes. However, it does not explicitly mention alternatives or when not to use this tool (e.g., for other countries or other ONS statistics), so it stops short of full exclusion guidance.

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