[marketsummary] Is money rotating into alts or back into BTC? By 7d relative strength vs BTC across our tracked crypto set. Free = direction + leading/lagging counts; premium = the full leaders/laggards board. Daily resolution; this is relative-strength rotation, NOT market-cap dominance. Not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| payment | No | ||
| session_token | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses daily resolution, the free/premium distinction, and a disclaimer ('Not advice'). It also clarifies the metric is relative-strength rotation. However, with no annotations present, the description fails to address important behavioral traits such as authentication requirements, rate limits, or that it is a read-only operation. The payment parameter is hinted at but not explained.
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 highly concise: three sentences that front-load the core purpose and include important clarifications. No extraneous information, every sentence adds value.
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?
Despite clear purpose, the description lacks details on return format, how to interpret 'direction + leading/lagging counts' vs 'full leaders/laggards board', and does not explain input parameters. Given no output schema and no annotations, the description should provide more context for correct use.
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 0%, and the description does not explain the two parameters ('payment' and 'session_token'). It implies that payment affects output (free vs premium), but this is not explicit. The description does not adequately compensate for the lack of schema documentation, leaving agents uncertain about parameter usage.
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 measures rotation between alts and BTC based on 7-day relative strength, using a specific verb-resource pair ('get rotation'). It distinguishes from sibling market summary tools by focusing on relative-strength rotation rather than other metrics like dominance or breadth.
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 clarifies that this is about rotation, not market-cap dominance, and notes daily resolution and that it is not advice. It mentions free vs premium features, giving context on access. However, it does not explicitly name alternative tools or specify when to use this over siblings like get_market_breadth.
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 market analysis or token safety, with clear descriptions that avoid overlap. Tools like find_longs and find_shorts are opposites, and other get_* tools each address unique metrics (e.g., buzz, attention shifts, smart money flow). No two tools have ambiguous boundaries.
Tools are prefixed by category (marketsummary__, tokensafety__, verify__), and most use a verb_noun pattern (e.g., get_liquidity, find_longs). However, there is some variation: 'ask_market', 'track_narrative', and longer names like 'attention_vs_price_divergence' break the pure 'get_' pattern. Overall, the naming is logical and predictable.
With 24 tools, the server covers a wide range of crypto market analysis, from general summaries to specific signals (e.g., conviction gap, smart money flow) and token safety. The count is well-scoped for the domain; each tool serves a clear purpose without being excessive.
The tool set is comprehensive for a market analysis server: it includes natural language querying, trend detection, sentiment, liquidity, whale activity, safety checks, and wallet verification for premium access. Missing trading actions are outside the stated purpose, so no gaps are apparent.