Get CoinVerdict's overall settled scoreboard across all coins: directional win rate, wins/losses/pushes, neutral (no-call) count, and how many calls are still open. Every verdict is graded 7 days later against BTC. Returns {board:{winrate,W,L,P,decided,neu}, since, open_calls}. Free, read-only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it is free and read-only, that verdicts are graded 7 days later against BTC, and specifies the return object. This provides behavioral context beyond the absence of annotations.
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, front-loaded with the action, and efficiently lists key information in two sentences without wasted words.
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 zero-parameter tool with no output schema, the description fully covers purpose, return structure, and behavioral traits, making it complete.
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?
There are no parameters, so baseline is 4. The description adds no parameter info but is not needed.
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 the overall settled scoreboard across all coins, with specific metrics. It distinguishes from sibling tools like get_verdict (per coin) and list_coins by specifying 'overall' and 'across all coins'.
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 the tool is for a high-level overview but does not explicitly state when to use it versus siblings. No alternatives or exclusions are mentioned.
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.