[marketsummary] Multi-horizon momentum for one token: 1h + 1d + 7d move + relative strength vs BTC, with an alignment verdict. Free = the alignment; premium = the full stack. 1h is the freshest but coarsest read (flagged if possibly-missing); horizons differ in resolution. 'No coverage' = off our radar.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | ||
| payment | No | ||
| session_token | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the 1h measure is the freshest but coarsest and may be missing, and explains 'No coverage' meaning. However, it does not cover error handling, permissions, or what happens if the ticker is invalid.
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 concise (two sentences) and front-loaded with purpose, but could be better structured with bullet points or clearer separation of concepts. No redundant text.
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 no output schema and moderate complexity, the description lists returned components but lacks details on output format, error cases, or pagination. The sibling tools list is large, but description does not help agent differentiate sufficiently.
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 0%, so the description must compensate. It implies 'ticker' is a token ticker and hints that 'payment' controls free vs premium stack, but does not explicitly describe 'session_token' or provide any format/validation details. Only marginal additional meaning.
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 it provides multi-horizon momentum for one token, including 1h, 1d, 7d moves, relative strength vs BTC, and an alignment verdict. This specific verb and resource set distinguishes it from sibling tools like 'get_ticker_dossier' or 'get_market_summary'.
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?
No explicit guidance on when to use this tool versus alternatives. It mentions free vs premium but does not explain when this tool is preferred over other market summary tools. No when-not-to-use or alternative naming.
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.