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

With no annotations provided, the description carries the full burden. It discloses that points are index levels, never prices; that response_mode 'summary' returns date + index_level points plus window change and 'full' adds gap flags; and that an honest 'insufficient_history' status is returned rather than a fabricated series. These are substantial behavioral traits beyond the schema.

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 dense and front-loaded with the core purpose, followed by critical disclaimers (base 100, not price). Each clause adds value, but some statements echo schema info, such as the period enum values and benchmark_id acceptance. Overall it is efficient, but slightly longer than strictly necessary.

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 no output schema and no annotations, the description is remarkably complete: it explains parameter behavior, response modes, error handling, alternatives, and scope limitations. It covers everything an agent needs to decide when to call this tool and how to interpret its results. Minor omissions like authentication are likely handled at the framework level.

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 adds meaningful conceptual clarity beyond the schema: it explains the 'same chained like-for-like series', the distinction between tier (buyer tier) and provider_type (billing-lens series with own base 100), and that provider_type series 'cut across provider/mcp'. This goes beyond the schema's dry enum descriptions, though some details (e.g., benchmark_id) are redundant with the schema.

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 opens with a specific verb and resource: 'the canonical DATED index SERIES ... of the AEPI'. It explicitly states every point is an index level (base 100), never a price, and contrasts itself with the whole-market economy series versus specific-capability tools. This clearly distinguishes it from siblings like get_price_index (point-in-time) and market_report/price_benchmark.

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?

It gives explicit usage context: 'Call this for the canonical DATED index SERIES (to chart or analyse movement)'. It also provides direct alternatives and exclusions: 'The economy index is whole-market by design — for pricing on a specific capability use market_report or price_benchmark.' Additionally, it explains when to use benchmark_id for a private custom benchmark's history.

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