get_versionsList all published versions for a crate in reverse chronological order. Returns version number, download count, and publish date.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Crate name |
| Name | Required | Description | Default |
|---|---|---|---|
| crate | Yes | Crate name | |
| versions | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds that the tool returns data in reverse chronological order, which is useful but not critical beyond annotations.
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 a single efficient sentence that conveys purpose and output. It contains no redundant phrases or unnecessary details.
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 the simple tool (one required param, list operation) and presence of an output schema, the description covers purpose, input, and output adequately. It lacks mention of error conditions or limits, but these are minor omissions for a straightforward tool.
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 100% with a single required parameter 'name' described as 'Crate name'. The description does not add any additional parameter details, so it meets the baseline for high coverage but provides no extra value.
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 clearly states the tool lists published versions for a crate in reverse chronological order, specifying the output fields (version number, download count, publish date). It distinguishes itself from sibling tools like get_crate or search_crates by focusing on versions.
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 no guidance on when to use this tool versus alternatives such as get_crate or search_crates. It lacks context about prerequisites or scenarios where this tool is preferred.
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.
The tool set includes several overlapping research/lookup tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) and multiple Polymarket tools, which could confuse an agent despite detailed descriptions. The boundaries between these tools are explained in the descriptions, but the sheer number of similar-purpose tools creates ambiguity.
Most tools follow a verb_noun pattern (e.g., search_crates, get_versions, validate_claim), but there are exceptions like entity_profile, deep_research, and bet_research, which break the pattern. The overall naming is readable and mostly consistent, with the polymarket_ and pipeworx_ prefixes providing grouping.
With 35 tools, the server is far too heavy for a focused service. The server name 'Crates' suggests a narrow domain, but only 5 tools relate to Rust crates, while the rest cover disparate areas (Pipeworx, Polymarket, memory management). This mismatch and high count make the tool surface unwieldy.
For the underlying Pipeworx/Polymarket domain that the majority of tools serve, the coverage is strong: lookup, grounded answers, research, entity profiles, comparisons, changes, claim validation, scanning, memory, subscriptions, tool discovery. Minor gaps exist (e.g., no direct summarization), but the set feels well-rounded for a data analysis agent.