get_case_roi_rankingRank Counter-Strike 2 cases by expected return on opening. Each entry gives the case price, expected value, return in basis points and the chance of an opening being profitable, all computed from current listing prices plus the key price. Cases whose contents are not sufficiently priced are excluded.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behavioral details: computation uses current listing prices and key price, excludes cases with insufficiently priced contents. No annotations exist, so description carries full burden, which it meets well.
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?
Two sentences, concise and front-loaded with the primary purpose. Every sentence adds value without redundancy.
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 parameterless tool with no output schema, the description fully explains the purpose, computed fields, data sources, and exclusion criteria. Nothing essential is omitted.
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?
No parameters, so baseline is 4. Description adds no parameter information, which is appropriate. It explains what the output contains, indirectly clarifying that no input is needed.
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?
Clearly states it ranks Counter-Strike 2 cases by expected return on opening, with specific computed fields. Distinct from sibling tools like browse_cases which likely don't provide ROI analysis.
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?
Describes what it does (rank cases by ROI) and implicitly when to use (when interested in ROI). No explicit when-not-to-use or alternatives, but context signals and sibling names make differentiation clear.
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.
Each tool targets a distinct aspect of CS2 cosmetics: browsing categories, searching, getting details, and ROI calculations. There is no overlap as browse/get/search verbs are clearly separated by resource type.
All tools follow a consistent verb_noun pattern (e.g., browse_bargains, get_case_roi_ranking, search_skins), using underscores and clear action words.
With 9 tools, the server covers the core functionality of browsing, searching, and analyzing CS2 skins and containers without being overly large or sparse.
The tool set covers browsing, searching, detail retrieval, and ROI analysis for cases and armory. A minor gap is the lack of user account operations or direct trading, but the server's scope is well-defined.