affiliate_firstpromoter_get_programme_performance

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

With no annotations, the description carries full transparency responsibility. It discloses that this is a read operation ('Fetch') and states the return type ('ProgrammePerformanceRow records'), which is useful. However, it does not mention pagination behavior, date range handling, defaults, or any edge cases, leaving notable behavioral gaps.

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 tight sentences: core function, usage examples, and output/pairing info. Every sentence adds value, and the structure front-loads the essential purpose.

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 8 parameters, no output schema, and no annotations, the description covers purpose, use cases, and sibling relationships but leaves parameter specifics, pagination, and detailed return shape underspecified. It is adequate for tool selection but not fully sufficient for confident invocation without additional inference.

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 0%, so the description must compensate. It adds indirect hints: 'by date' implies from/to semantics, 'per-publisher' implies publisherId filtering, and 'brand's programme' ties brand to the programme. It also suggests using list_media_partners to discover publisher ids. However, limit/cursor/offset and programmeId are left unexplained, so compensation is incomplete.

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 uses a specific verb ('Fetch') and resource ('per-publisher performance for the brand's programme at FirstPromoter'), listing concrete metrics (clicks, conversions, gross sale, commission) and date scoping. This clearly distinguishes it from sibling tools like list_transactions or get_earnings_summary.

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 explicit user query examples ('how is each publisher performing on FirstPromoter?', 'show me the top-earning partners last month') and frames the core use case as a per-publisher rollup. It also names complementary tools (list_media_partners for publisher ids, list_transactions for transaction-level drill-down), providing clear when-to-use and alternative guidance.

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