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list_open_ideas

Returns approved prediction cards with future deadlines, including title, category, and resolution criteria. Limit results as needed.

Instructions

List currently-open prediction cards on the CalledIt feed. Returns approved ideas whose lock_at is in the future. Each item includes the title, one-liner, category, deadline, and resolution criteria.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax ideas to return (default 10).

Implementation Reference

  • src/index.ts:67-83 (registration)
    Registration of the 'list_open_ideas' tool via server.registerTool, including the description and input schema with an optional 'limit' parameter (1-50, default 10).
    server.registerTool(
      'list_open_ideas',
      {
        description:
          'List currently-open prediction cards on the CalledIt feed. ' +
          "Returns approved ideas whose lock_at is in the future. Each item " +
          'includes the title, one-liner, category, deadline, and resolution criteria.',
        inputSchema: {
          limit: z
            .number()
            .int()
            .min(1)
            .max(50)
            .optional()
            .describe('Max ideas to return (default 10).'),
        },
      },
  • Handler function for list_open_ideas. Queries Supabase 'ideas' table for approved ideas with future lock_at, returning id, title, one_liner, category, lock_at, resolve_at, and resolution_criteria. Limited by the optional cap parameter.
      async ({ limit }) => {
        const cap = Math.min(limit ?? 10, 50);
        const { data, error } = await sb
          .from('ideas')
          .select(
            'id,title,one_liner,category,lock_at,resolve_at,resolution_criteria',
          )
          .eq('status', 'approved')
          .gt('lock_at', new Date().toISOString())
          .order('created_at', { ascending: false })
          .limit(cap);
        if (error) {
          return {
            content: [{ type: 'text', text: `error: ${error.message}` }],
            isError: true,
          };
        }
        const ideas = (data ?? []).map((r) => ({
          id: r.id,
          title: r.title,
          oneLiner: r.one_liner,
          category: r.category,
          lockAt: r.lock_at,
          resolveAt: r.resolve_at,
          resolutionCriteria: r.resolution_criteria,
        }));
        return {
          content: [{ type: 'text', text: JSON.stringify(ideas, null, 2) }],
        };
      },
    );
  • Zod schema for the optional input parameter: 'limit' (integer, 1-50, default 10).
    limit: z
      .number()
      .int()
      .min(1)
      .max(50)
      .optional()
      .describe('Max ideas to return (default 10).'),
Behavior3/5

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

Discloses filtering criteria and output fields, but lacks details on pagination, ordering, or authentication requirements.

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?

Two sentences, no wasted words, purpose stated first.

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

Completeness5/5

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

Given the simplicity and lack of output schema, description adequately explains what the tool returns and the criteria. No significant gaps.

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 already fully documents the only parameter; description adds no additional semantic meaning.

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?

Clearly describes verb (list) and resource (open prediction cards), specifies filtering criteria and output fields. Distinguishable from sibling tools.

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?

No explicit usage guidance; context is clear but without stating when to use vs alternatives.

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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