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vybsly_odds

Get live betting odds from top bookmakers for NBA, NFL, MLB, NHL, UFC, and MMA. Filter by team or fighter for targeted analysis.

Instructions

Live sports betting odds from multiple bookmakers (FanDuel, DraftKings, BetMGM). Useful for sports analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNonba, nfl, mlb, nhl, ufc, mma
teamNoFilter by team or fighter name

Implementation Reference

  • Tool definition/schema for 'vybsly_odds' — defines name, description, and inputSchema with optional 'sport' and 'team' properties.
    {
      name: 'vybsly_odds',
      description: 'Live sports betting odds from multiple bookmakers (FanDuel, DraftKings, BetMGM). Useful for sports analysis.',
      inputSchema: {
        type: 'object',
        properties: {
          sport: { type: 'string', description: 'nba, nfl, mlb, nhl, ufc, mma' },
          team: { type: 'string', description: 'Filter by team or fighter name' }
        }
      }
    },
  • Handler for 'vybsly_odds' — builds params from args.sport and args.team, then calls vybslyCall('/odds', params).
    case 'vybsly_odds': {
      const params = {};
      if (args.sport) params.sport = args.sport;
      if (args.team) params.team = args.team;
      result = await vybslyCall('/odds', params);
      break;
    }
  • vybslyCall helper function — makes authenticated HTTP GET requests to the Vybsly API with query params and returns JSON.
    async function vybslyCall(path, params = {}) {
      const qs = new URLSearchParams(params).toString();
      const url = `${VYBSLY_BASE}${path}${qs ? '?' + qs : ''}`;
      const headers = { 'Accept': 'application/json' };
      if (API_KEY) headers['X-API-Key'] = API_KEY;
      const res = await fetch(url, { headers });
      if (!res.ok) {
        const text = await res.text();
        throw new Error(`Vybsly API ${res.status}: ${text.slice(0, 300)}`);
      }
      return res.json();
    }
  • index.js:417-417 (registration)
    Tool registration via ListToolsRequestSchema handler — returns the TOOLS array (which includes 'vybsly_odds' at index).
    server.setRequestHandler(ListToolsRequestSchema, async () => ({ tools: TOOLS }));
  • Main CallToolRequestSchema handler — switch-case dispatches to tool handlers including 'vybsly_odds' case at line 479.
    server.setRequestHandler(CallToolRequestSchema, async (req) => {
      const { name, arguments: args } = req.params;
      try {
        let result;
        switch (name) {
          case 'vybsly_search':
            result = await vybslyCall('/search', {
              q: args.query,
              limit: args.limit || 10,
              ...(args.mode && { mode: args.mode }),
              ...(args.strict && { strict: 'true' }),
              ...(args.research && { research: 'true' }),
              ...(args.news && { news: 'true' }),
              ...(args.educational && { educational: 'true' }),
              ...(args.source && { source: args.source }),
              ...(args.lang && { lang: args.lang }),
              ...(args.strict_fallback && { strict_fallback: args.strict_fallback })
            });
            break;
          case 'vybsly_knowledge':
            result = await vybslyCall('/knowledge', {
              q: args.query,
              limit: args.limit || 10,
              ...(args.strict && { strict: 'true' }),
              ...(args.research && { research: 'true' })
            });
            break;
          case 'vybsly_extract':
            result = await vybslyCall('/extract', { url: args.url, ...(args.format && { format: args.format }) });
            break;
          case 'vybsly_ask': {
            const res = await fetch(`${VYBSLY_BASE}/ask`, {
              method: 'POST',
              headers: { 'Content-Type': 'application/json', ...(API_KEY && { 'X-API-Key': API_KEY }) },
              body: JSON.stringify({ question: args.question, max_sources: args.max_sources || 5 })
            });
            result = await res.json();
            break;
          }
          case 'vybsly_stocks':
            result = await vybslyCall('/stocks', { symbols: args.symbols });
            break;
          case 'vybsly_crypto':
            result = await vybslyCall('/crypto', { symbol: args.symbol });
            break;
          case 'vybsly_weather':
            result = await vybslyCall('/weather', { city: args.city });
            break;
          case 'vybsly_news':
            result = await vybslyCall('/news', { q: args.query, hours: args.hours || 24 });
            break;
          case 'vybsly_odds': {
            const params = {};
            if (args.sport) params.sport = args.sport;
            if (args.team) params.team = args.team;
            result = await vybslyCall('/odds', params);
            break;
          }
          case 'vybsly_geocode':
            result = await vybslyCall('/geocode', { q: args.address });
            break;
          case 'vybsly_directions':
            result = await vybslyCall('/directions', { from: args.from, to: args.to });
            break;
          default:
            throw new Error(`Unknown tool: ${name}`);
        }
        return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
      } catch (e) {
        return {
          content: [{ type: 'text', text: `Error calling ${name}: ${e.message}` }],
          isError: true
        };
      }
    });
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. However, it fails to mention limitations such as data freshness, latency, coverage scope, error handling, or what happens when no odds are found. The behavior is under-specified for a live data tool.

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 concise, with two sentences that front-load the core purpose and utility. No extraneous information is present, making it efficient and easy to parse.

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 lack of output schema and annotations, the description should provide more completeness about return values, coverage, or typical use. It covers the basic purpose but leaves gaps about behavior and output format, which are critical for an agent.

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%, with each parameter described adequately. The description adds context about the bookmakers but does not enhance the understanding of the parameters beyond what the schema provides. Baseline 3 applies.

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

Purpose5/5

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

The description clearly states it provides live sports betting odds from named bookmakers (FanDuel, DraftKings, BetMGM) and specifies its utility for sports analysis. The verb 'get' is implied, and the resource is well-defined, distinguishing it from sibling tools which cover different domains.

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 mentions 'useful for sports analysis' as a guidance, but does not provide explicit when-to-use or when-not-to-use instructions, nor does it compare with alternatives (though no direct alternatives exist among siblings). It lacks context like prerequisites or suggested use cases.

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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