[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?
No annotations are provided, so the description carries the full burden. It adds valuable behavioral context: '1h is the freshest but coarsest read (flagged if possibly-missing)', 'horizons differ in resolution', and the meaning of 'No coverage'. This goes beyond a simple function statement and informs the agent about data caveats.
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 somewhat long but front-loaded with the primary purpose. Each sentence adds value, including pricing tiers, data freshness caveats, and coverage status. It could be tightened, but it remains organized and efficient.
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?
With no output schema, the description explains return value components (momentum horizons, relative strength, alignment verdict) and covers edge cases like 'No coverage'. However, it omits details about payment/session_token usage and any potential error conditions, leaving some context gaps for a 3-parameter 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 0%, so the description must compensate for explaining parameters. It only indirectly references 'ticker' via 'one token' and does not explain 'payment' or 'session_token' at all, despite mentioning free vs premium which hints at payment semantics. This leaves key parameters underdocumented.
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's function: 'Multi-horizon momentum for one token' with specific horizons (1h, 1d, 7d) and relative strength vs BTC, plus an alignment verdict. This specific verb+resource structure distinguishes it from siblings like get_market_summary or get_ticker_dossier.
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 implies usage for token-specific momentum analysis with 'one token' and the momentum horizons, but it does not explicitly state when to use this tool instead of alternatives or mention exclusions. No sibling comparisons or when-not-to-use guidance is given.
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 metric or action: attention shifts, buzz score, trending, and narrative tracking measure different facets; longs, shorts, and setups use different strategies; market regime, breadth, and summary are clearly separated. No two tools appear to produce the same output.
All tools follow a consistent pattern: a subsystem prefix (marketsummary__, tokensafety__, verify__) followed by an imperative verb_noun in snake_case. Verbs are predictable (get, find, track, ask, check, request, verify) and objects are clear, making the naming highly uniform.
24 tools is above the typical 3-15 range, but the server covers a broad market-intelligence domain with distinct feature areas. The tools are namespaced by subsystem, which helps agents navigate, but the volume still adds selection overhead.
The set covers market analysis, trending, sentiment, trade setups, token safety, and wallet verification for premium access. Minor gaps exist (e.g., no direct price/OHLC tool or token search), but agents can work around them using the provided tools.