ygo_market_query

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

With no annotations supplied, the description carries the full burden and does so: it discloses the ranking data source (TCGPlayer/Cardmarket via YGOPRODeck), a geographic bias ('Ranking is US-based') and why, the enrichment cap ('covers the top 3 results'), and instructs the agent to surface priceBasis, confidence and data caveats. These are non-obvious operational traits an agent could not infer from 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 most important routing information is front-loaded in the first sentence, which is good. However, the no-memory instruction is stated twice ('Never answer "most expensive / rising" from memory' and the closing 'Do not answer from memory; call this tool first'), and the middle section packs several unrelated caveats into a single run-on sequence, so the text is longer than its content requires.

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 22-parameter tool with no output schema, the description covers the critical unknowns: data provenance, ranking bias, enrichment scope and the instruction to report confidence and caveats. What it omits is any sense of result shape or how the correlated news/banlist/meta context is returned, which matters more here because no output schema documents it.

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 and the description earns an increment by adding rationale the schema lacks — why liquidity_adjusted exists ('price × demand on log scales'), what includeMarkets enriches and its explain default, and the purpose of minWeeklyViews ('drop collector-only cards nobody actually buys'). It stops short of explaining the interaction between intent and sortBy beyond one clause.

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 opening line gives a specific verb-and-resource scope ('ranks and filters the entire card pool by price, demand and measured movement') and immediately bounds it negatively ('NOT about one named card'). The worked example queries ('which card is the most expensive', 'what is hot under $5') let an agent match user phrasing to this tool without opening the 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?

Explicit routing is provided in both directions: use this for pool-level market questions, use ygo_check_prices for a single card's shop-by-shop quotes. It also names a conditional alternative within the tool itself (sortBy: 'liquidity_adjusted' when the user means 'expensive but actually sellable') and an exclusion ('Never answer from memory').

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