Get today's verdict for ALL covered coins in one call — the full docket: each coin's current stance (overweight/neutral/underweight), price, and W/L/P settled record. Use this to scan the whole market at once instead of calling get_verdict per coin. Returns {coins:[{symbol,stance,price_usd,board}], as_of}. Free, read-only, not advice.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states 'Free, read-only, not advice' and outlines return structure. Could mention rate limits or data freshness, but still good.
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?
Concise at three lines, clearly structured with bullet-like return format. Slightly verbose metaphor 'docket' but effective. Front-loaded with purpose.
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, description adequately explains return structure ({coins:[{symbol,stance,price_usd,board}], as_of}). Missing error or staleness info, but sufficient for a simple zero-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?
No parameters exist, so schema coverage is 100%. Baseline 4 applies as description adds meaning about the tool's scope and return format beyond schema.
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 retrieves today's verdict for all covered coins in one call, listing returned fields (stance, price, W/L/P record). It distinguishes itself from the sibling 'get_verdict' by noting it covers all coins at once.
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?
Explicitly advises using this tool instead of calling 'get_verdict' per coin to scan the whole market at once, providing clear when-to-use guidance.
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 serves a distinct purpose: per-coin vs whole-market verdicts, per-coin vs overall track records, a leaderboard, and a symbol discovery tool. No two tools overlap in their primary function, and descriptions reinforce the differences.
Five of six tools follow the 'get_' + noun pattern (get_kol_leaderboard, get_market_overview, get_receipts, get_track_record, get_verdict), but list_coins deviates by using 'list_' instead of 'get_'. The pattern is otherwise very consistent.
Six tools is right-sized for a read-only research API. Each tool addresses a clear aspect of the domain (discovery, current verdicts, historical performance, market-wide summary, and influencer data) without unnecessary bloat or missing essentials.
The tool set covers the full lifecycle of a verdict-based research service: discovery (list_coins), current verdicts for one coin (get_verdict) and all coins (get_market_overview), settled performance for one coin (get_track_record) and overall (get_receipts), plus a unique KOL leaderboard. No obvious gaps for the stated purpose.