List all CryptoPunk traits with their counts. Optionally filter by type to see how many punks of that type have each trait. Rate limit: 10 per 10 min (read bucket — shared with browse_types, get_punk_details, get_listings, get_floor_price, get_bids_for_punk, get_bids_for_merkle_root).
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter counts to a specific type (e.g. 'Male', 'Zombie') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation is supplemented with the rate limit (10 per 10 min) and the shared read bucket, adding valuable behavioral context beyond the annotation. No contradictory statements exist.
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 compact: one sentence for the core purpose and one sentence for the optional filter and rate limit. Every word serves a purpose, with no redundancy or filler.
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 simple list tool with one optional parameter, this description fully covers selection and invocation. It explains the result (trait counts), filter behavior, and rate limiting, making it complete despite no output schema.
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?
The schema already describes the type parameter, but the description enriches it by clarifying the output: 'see how many punks of that type have each trait.' This adds meaning beyond the schema's filter description.
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 begins with a specific verb+resource: 'List all CryptoPunk traits with their counts.' This clearly distinguishes the tool from siblings like browse_types (traits vs. types) and filter_punks, making its purpose unambiguous.
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 provides clear context by explaining the optional type filter and the rate limit shared with other read tools. However, it does not explicitly state when to prefer this over browse_types or filter_punks, relying on implied differentiation rather than direct alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct resource or action: trait/type browsing, punk metadata, listings/floor price, bids by root/punk, Merkle computation/filtering/resolution, and bid recommendations. The related Merkle tools have clear boundaries: compute builds a root from IDs, filter returns IDs for a trait selection, and resolve reverses a root only if it has bids.
All tool names follow a consistent `verb_noun` pattern in snake_case (e.g., browse_traits, get_floor_price, resolve_merkle_root). The two bid lookup tools use the same `get_bids_for_X` structure, reinforcing predictability.
Eleven tools is well within the ideal 3-15 range and each covers a necessary facet of the CryptoPunks domain—from market data (listings, floor) to trait-based bid analysis (merkle roots, recommendations). No redundancy or bloat.
The tool surface covers the full read-side lifecycle: viewing traits/types/punks, checking market prices/listings, analyzing existing bids, and supporting trait-based bid strategies through Merkle root operations and recommendations. It lacks write actions (e.g., placing bids), but the server's purpose is clearly analytical, so no obvious operational gap exists.