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m9k_full

Read-onlyIdempotent

Retrieve complete content of specific conversation chunks by their IDs. Use after search operations to access full context from indexed conversations in the Melchizedek MCP server.

Instructions

Retrieve full content of chunks by IDs. Use after m9k_search to get complete context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chunkIdsYesChunk IDs to retrieve in full

Implementation Reference

  • Handler function for the m9k_full tool which retrieves full chunk content from the database based on provided IDs.
      async ({ chunkIds }) => {
        const placeholders = chunkIds.map(() => '?').join(',');
        const stmt = ctx.db.prepare(
          `SELECT id, session_id, idx, kind, user_content, assistant_content, hash, timestamp, token_count, tags, metadata_json
           FROM conv_chunks WHERE id IN (${placeholders}) AND deleted_at IS NULL`,
        );
        const rows = stmt.all(...chunkIds);
        return {
          content: [{ type: 'text' as const, text: JSON.stringify(rows) }],
        };
      },
    );
  • Zod input schema definition for the m9k_full tool, validating an array of chunk IDs.
    inputSchema: {
      chunkIds: z.array(z.string()).min(1).max(20).describe('Chunk IDs to retrieve in full'),
    },
  • Registration block for the m9k_full tool using the MCP server instance.
    server.registerTool(
      'm9k_full',
      {
        description:
          'Retrieve full content of chunks by IDs. Use after m9k_search to get complete context.',
        inputSchema: {
          chunkIds: z.array(z.string()).min(1).max(20).describe('Chunk IDs to retrieve in full'),
        },
        annotations: {
          readOnlyHint: true,
          destructiveHint: false,
          idempotentHint: true,
          openWorldHint: false,
        },
      },
Behavior3/5

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

Annotations cover safety (readOnlyHint, idempotentHint). Description adds 'full content' distinction versus partial results, but omits return format, rate limits, or the 20-item max constraint implications.

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 with zero waste: first states purpose, second provides workflow context. Front-loaded with action verb and logically structured.

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?

Complete for a simple retrieval tool given annotations cover safety profile. Addresses purpose, sibling relationship, and parameter intent. No output schema exists, so return value description is not expected.

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 has 100% coverage describing 'Chunk IDs to retrieve in full'. Description mentions 'by IDs' aligning with the parameter, but adds no syntax, format examples, or behavioral constraints beyond schema.

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?

Specific verb ('Retrieve'), resource ('chunks by IDs'), and scope ('full content') clearly stated. Differentiates from sibling m9k_search by emphasizing completeness versus search results.

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

Usage Guidelines5/5

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

Explicitly names sibling tool in workflow: 'Use after m9k_search to get complete context'. Provides clear temporal guidance (when to use) and rationale (complete context).

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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