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generate_transcripts

Generate speaker notes and transcripts for slides in an existing presentation to create talking points for delivery.

Instructions

Generate speaker notes or transcripts for slides in an existing presentation. Use this when the deck visuals are ready and you need talking points for delivery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presentation_idYesPresentation whose slides need speaker notes.
slide_idsNoOptional subset of slide identifiers to process.

Implementation Reference

  • src/index.js:323-346 (registration)
    Registration of the 'generate_transcripts' tool with input schema (presentation_id required, slide_ids optional). The handler delegates to the remote MCP endpoint via callRemoteTool.
    server.registerTool(
      "generate_transcripts",
      {
        description:
          "Generate speaker notes or transcripts for slides in an existing presentation. Use this when the deck visuals are ready and you need talking points for delivery.",
        inputSchema: {
          presentation_id: z
            .string()
            .min(1)
            .describe("Presentation whose slides need speaker notes."),
          slide_ids: z
            .array(z.string())
            .optional()
            .describe("Optional subset of slide identifiers to process."),
        },
      },
      async (args) => {
        try {
          return await callRemoteTool("generate_transcripts", args);
        } catch (error) {
          return normalizeError(error);
        }
      },
    );
  • Input schema for generate_transcripts: requires presentation_id (string), optionally accepts slide_ids (array of strings).
    inputSchema: {
      presentation_id: z
        .string()
        .min(1)
        .describe("Presentation whose slides need speaker notes."),
      slide_ids: z
        .array(z.string())
        .optional()
        .describe("Optional subset of slide identifiers to process."),
    },
  • Handler for generate_transcripts: proxies call to the remote Alai MCP endpoint via callRemoteTool, with error normalization.
    async (args) => {
      try {
        return await callRemoteTool("generate_transcripts", args);
      } catch (error) {
        return normalizeError(error);
      }
    },
  • Generic remote tool caller used by generate_transcripts to forward the request to the Alai MCP endpoint.
    async function callRemoteTool(name, args) {
      const client = new Client(
        { name: "alai-mcp-wrapper", version: "1.0.2" },
        { capabilities: {} },
      );
      const transport = new StreamableHTTPClientTransport(new URL(REMOTE_MCP_URL), {
        requestInit: {
          headers: createRemoteHeaders(),
        },
      });
    
      try {
        await client.connect(transport);
        return await client.callTool({
          name,
          arguments: args,
        });
      } finally {
        await transport.close().catch(() => {});
        await client.close().catch(() => {});
      }
    }
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. It fails to mention whether the tool overwrites existing notes, is additive, or requires any permissions. The side effects and safety of the operation are unclear.

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 (two sentences) and well-structured, with the first sentence stating purpose and the second providing usage context. No unnecessary words.

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?

The tool has no output schema, so the description should indicate what is returned (e.g., updated presentation, success message). It does not, leaving agents uncertain about the outcome. Additionally, it does not clarify if the operation is synchronous or async, despite a sibling tool for generation status.

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?

Input schema coverage is 100%, with clear descriptions for both parameters. The description does not add significant meaning beyond the schema, except hinting that the output is speaker notes or transcripts. Baseline 3 is appropriate.

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 the tool's purpose: 'Generate speaker notes or transcripts for slides in an existing presentation.' It uses a specific verb ('generate') and resource ('speaker notes or transcripts for slides'), and distinguishes from sibling tools like create_slide and generate_presentation.

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

Usage Guidelines4/5

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

The description provides usage guidance: 'Use this when the deck visuals are ready and you need talking points for delivery.' It implies when to use but does not explicitly mention when not to use or suggest alternatives, leaving some ambiguity.

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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