List all CryptoPunk type categories with their counts. Rate limit: 10 per 10 min (read bucket — shared with browse_traits, get_punk_details, get_listings, get_floor_price, get_bids_for_punk, get_bids_for_merkle_root).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description goes beyond by specifying a concrete rate limit (10 per 10 min) and naming the shared read bucket with six other tools. This adds valuable operational behavior not present in the annotations, with no contradictions.
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 two sentences: the first states the core action, and the second adds a critical operational constraint. It is succinct, front-loaded, and every word earns its place with no fluff.
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 zero-parameter, read-only listing tool, the description is fully complete: it states exactly what it returns (type categories with counts) and a critical operational detail (shared rate limit). No output schema is necessary because the return value is straightforward.
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 tool has zero parameters, and the input schema is empty, so the description does not need to explain parameter semantics. The baseline for zero parameters is 4, and the description appropriately focuses on functionality and rate limits.
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 starts with 'List all CryptoPunk type categories with their counts,' which uses a specific verb ('List'), a clear resource ('type categories'), and the output ('counts'). This distinguishes it from sibling tool browse_traits, which likely handles trait categories.
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 specifying that it lists all type categories, which implies when to use it. However, it does not explicitly mention alternatives or exclusions, such as 'for traits, use browse_traits instead.' The rate limit sharing information gives additional operational context but not direct usage guidance.
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.