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get_pool_history

Retrieve historical pool data including past winners, price changes, pool sizes, and share distribution to analyze trends and calibrate competition strategies.

Instructions

Get historical pool results. Shows past winners, price changes, pool sizes, and share distribution. Use this to calibrate your strategy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of historical pools to return (max 100)

Implementation Reference

  • The get_pool_history tool handler that fetches historical pool data via a GET request to the Conviction.fm API, processes the results, and returns them in a formatted string.
    // ── Tool: get_pool_history ──
    
    server.tool(
      "get_pool_history",
      "Get historical pool results. Shows past winners, price changes, pool sizes, and share distribution. Use this to calibrate your strategy.",
      {
        limit: z.number().min(1).max(100).default(20).describe("Number of historical pools to return (max 100)"),
      },
      async ({ limit }) => {
        const data = (await apiGet(`pool-state?mode=history&limit=${limit}`)) as any;
        const pools = data.pools || [];
    
        if (pools.length === 0) {
          return { content: [{ type: "text", text: "No historical data available yet." }] };
        }
    
        const lines = pools.map((p: any) => {
          const aChange = p.tokenA?.priceChange24h?.toFixed(2) ?? "?";
          const bChange = p.tokenB?.priceChange24h?.toFixed(2) ?? "?";
          const total = p.totalPoolUsdc?.toFixed(0) ?? "?";
          const aShare = p.tokenA?.poolSharePercent?.toFixed(0) ?? "?";
          const bShare = p.tokenB?.poolSharePercent?.toFixed(0) ?? "?";
          return `${p.tokenPairKey}: Winner=${p.winnerTokenId ?? "?"} | ${p.tokenA?.id}=${aChange}% ${p.tokenB?.id}=${bChange}% | $${total} pool (${aShare}/${bShare})`;
        });
    
        return {
          content: [
            {
              type: "text",
              text: `# Pool History (${pools.length} results)\n\n${lines.join("\n")}\n\n_Use this data to calibrate your strategy._`,
            },
          ],
        };
      }
    );
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what data is returned but doesn't describe important behavioral traits: whether this is a read-only operation (implied but not stated), potential rate limits, authentication requirements, error conditions, or response format. The description adds some context about data content but misses key operational details.

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?

The description is perfectly concise: two sentences that efficiently convey purpose and usage. Every word earns its place - the first sentence explains what the tool does and what data it returns, the second provides strategic context. No wasted words or redundant information.

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

Completeness3/5

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

Given the tool's moderate complexity (historical data retrieval with one parameter), no annotations, and no output schema, the description is minimally adequate. It explains what data is returned but doesn't cover the response structure, error handling, or operational constraints. For a tool with no annotations or output schema, it should provide more complete context about the return values and behavioral characteristics.

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?

The schema description coverage is 100% (the single parameter 'limit' is fully documented in the schema), so the baseline is 3. The description doesn't add any parameter-specific information beyond what's in the schema - it doesn't explain how 'limit' affects the historical data retrieval or provide additional context about parameter usage.

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 clearly states the tool's purpose: 'Get historical pool results' with specific details about what data it returns (past winners, price changes, pool sizes, share distribution). It distinguishes itself from sibling tools like 'get_pools' by focusing on historical data rather than current pools. However, it doesn't explicitly contrast with all siblings, keeping it at a 4 rather than 5.

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 description provides implied usage guidance: 'Use this to calibrate your strategy' suggests it's for analytical purposes. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_pools' (which might show current pools) or other data tools. No explicit exclusions or prerequisites are mentioned.

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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