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PaulieB14

Limitless MCP

by PaulieB14
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JavaScript
Remote

get_daily_protocol_stats

Retrieve daily protocol statistics including volume, trades, fees, splits, merges, and redemptions as a time series to analyze market performance.

Instructions

Get daily protocol stats (volume, trades, fees, splits, merges, redemptions) across both market types as a time series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days to return

Implementation Reference

  • mcp-server/src/index.ts:528-563 (handler)
    The handler for the 'get_daily_protocol_stats' tool. It queries both market types for daily snapshots, merges the data by dayId, and returns the aggregated time series.
    async ({ days }) => {
  try {
    const snapshotQuery = `{
      globalDailySnapshots(first: ${days}, orderBy: dayId, orderDirection: desc) {
        dayId date totalTradesCount totalVolumeUSD totalFeesUSD
        totalSplits totalMerges totalRedemptions
      }
    }`;

    const { simple, negrisk } = await queryBoth(snapshotQuery, snapshotQuery);

    // Merge by dayId
    const merged = new Map<number, any>();
    for (const s of simple.globalDailySnapshots || []) {
      merged.set(s.dayId, {
        dayId: s.dayId,
        date: s.date,
        simpleTradesCount: s.totalTradesCount,
        simpleVolumeUSD: s.totalVolumeUSD,
        simpleFeesUSD: s.totalFeesUSD,
        simpleSplits: s.totalSplits,
        simpleMerges: s.totalMerges,
        simpleRedemptions: s.totalRedemptions,
        negriskTradesCount: "0",
        negriskVolumeUSD: "0",
        negriskFeesUSD: "0",
        negriskSplits: "0",
        negriskMerges: "0",
        negriskRedemptions: "0",
      });
    }
    for (const n of negrisk.globalDailySnapshots || []) {
      const existing = merged.get(n.dayId);
      if (existing) {
        existing.negriskTradesCount = n.totalTradesCount;
        existing.negriskVolumeUSD = n.totalVolumeUSD;
  • mcp-server/src/index.ts:519-527 (registration)
    Registration of the 'get_daily_protocol_stats' tool in the MCP server.
    server.registerTool(
  "get_daily_protocol_stats",
  {
    description:
      "Get daily protocol stats (volume, trades, fees, splits, merges, redemptions) across both market types as a time series.",
    inputSchema: {
      days: z.number().default(30).describe("Number of days to return"),
    },
  },

Tool Definition Quality

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It successfully discloses the return format ('time series') and enumerates the specific data categories returned, which helps the agent understand output structure. However, it omits operational details like read-only status, rate limits, or caching behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single, information-dense sentence. Every clause earns its place: the verb/resource ('Get daily protocol stats'), the metric enumeration in parentheses, the scope qualifier ('across both market types'), and the format ('as a time series'). Zero redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has only one optional parameter with 100% schema coverage and no output schema, the description successfully compensates by detailing what metrics are returned. However, it could briefly clarify what 'protocol' means in this domain versus market-level data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (the 'days' parameter is fully documented in the schema). The description mentions 'daily' which conceptually links to the 'days' parameter, but doesn't add explicit syntax guidance, validation limits, or usage examples beyond what the schema provides. Baseline 3 is appropriate for high-coverage schemas.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and resource ('daily protocol stats') and clearly lists the returned metrics (volume, trades, fees, splits, merges, redemptions). It distinguishes from market-specific sibling tools by emphasizing 'protocol' level and 'across both market types,' though it doesn't explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'across both market types' implicitly signals this aggregates data rather than querying individual markets (unlike get_market_daily_snapshots), but lacks explicit when-to-use guidance or prerequisites. The agent must infer this is for aggregated time-series analysis versus per-market inspection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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