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

Discloses economics (5 tokens per query), the failure mode (refused below balance, returning your balance), authorization state (403 until a human claims the workspace), and paging behavior. These are non-obvious operational traits an agent must know before calling, and they are consistent with readOnlyHint=false given the token spend.

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, followed by cost, paging, then the prerequisite. Every sentence carries information, though the token-economics sentence packs three distinct facts into one dense clause.

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?

No output schema exists, and the description compensates by characterizing the return shape (data points with contributor counts and recency). Cost, prerequisites, and paging are all covered, so nothing an agent needs to invoke 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?

Schema coverage is 100%, so limit, offset and vertical are already fully documented. The description only restates that vertical is optional and that limit/offset do paging, adding no syntax or format detail beyond the schema; baseline 3 applies.

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 and resource ('Read price data other workspaces have shared') and immediately scopes the result (newest data points, optional vertical, contributor count and freshness). This is clearly distinguishable from the sibling contribute_price_data (writes data) and list_jale_contributions (your own contributions).

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?

Gives explicit conditions: you need a claimed workspace, sandbox keys get 403, below 5 tokens the call is refused, and contribute_price_data is the way to earn tokens. It does not compare against other price-reading siblings such as get_x402_price_index, browse_catalog, or recommend_jale_price, so the 'when not to use' side is incomplete.

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