Returns the top N cryptocurrencies by a chosen ranking method: tvr_score (fundamental strength), most_undervalued (largest positive fair value gap), or most_overvalued (largest negative fair value gap). Data from True Value Rankings (truevaluerankings.com).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of coins to return (1-10, default 5) | |
| rank_by | No | Ranking method: tvr_score, most_undervalued, or most_overvalued | tvr_score |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It clearly implies a read-only operation ('Returns') and adds provenance (True Value Rankings). It does not state potential side effects or limitations, but the tool's simple read nature makes this adequate.
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, front-loaded with the core purpose, and includes necessary detail without redundancy. No filler words or irrelevant information.
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 two-parameter tool with no output schema, the description covers the essential functionality clearly. It omits return format details, but these are often self-evident for a top-N list. Sibling discrimination is provided via ranking method context.
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 parameter descriptions exist for both count and rank_by. The description adds significant semantic value by explaining what each ranking method means, which the enum schema only lists. This goes beyond the bare schema definitions.
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 returns the top N cryptocurrencies with a specified ranking method, listing three explicit options. This distinguishes it from sibling tools like get_custom_ranking or get_tvr_score, which focus on different functionality.
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 context on when to use the tool by explaining the ranking methods and data source, but does not explicitly mention when not to use it or mention alternatives. The context is clear enough for an agent to infer usage, but it lacks exclusions or direct comparisons to siblings.
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.
Most tools target distinct functions (listing, scoring, valuation, comparison, rankings, methodology, history). However, get_tvr_estimated_value and get_tvr_score overlap significantly, as get_tvr_score already includes the valuation data. Compare_coins and get_comparison_report are similar but differentiated by depth.
All tools follow a consistent verb_noun pattern, primarily using 'get_' with a descriptive noun. This makes the tool names predictable and easy to navigate.
11 tools is well-scoped for a cryptocurrency analysis service, covering the full range of querying, comparison, and premium features without excess.
The tool set covers the major use cases: discovering coins, obtaining scores and valuations, comparing, ranking, historical tracking, portfolio analysis, and understanding methodology. No significant gaps are apparent.