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Read Topic

discourse_read_topic

Retrieve topic metadata and initial posts from Discourse forums to analyze discussions and gather information for AI agents.

Instructions

Read a topic metadata and first N posts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topic_idYes
post_limitNo
start_post_numberNoStart from this post number (1-based)

Implementation Reference

  • Executes the tool logic: fetches topic metadata and posts from Discourse API using the selected site's client, handles pagination in batches, formats output as markdown-like text with title, posts, and link, includes error handling.
    async ({ topic_id, post_limit = 5, start_post_number }, _extra: any) => {
      try {
        const { base, client } = ctx.siteState.ensureSelectedSite();
        const start = start_post_number ?? 1;
    
        // First request to load metadata/title and initial chunk
        let current = start;
        let fetchedPosts: Array<{ number: number; username: string; created_at: string; content: string }> = [];
        let slug = "";
        let title = `Topic ${topic_id}`;
        let category = "";
        let tags: string[] = [];
    
        const maxBatches = 10; // safety guard
        const limit = Number.isFinite(ctx.maxReadLength) ? ctx.maxReadLength : 50000;
        for (let i = 0; i < maxBatches && fetchedPosts.length < post_limit; i++) {
          // Ask for raw content when possible
          const url = current > 1 ? `/t/${topic_id}.json?post_number=${current}&include_raw=true` : `/t/${topic_id}.json?include_raw=true`;
          const data = (await client.get(url)) as any;
          if (i === 0) {
            title = data?.title || title;
            category = data?.category_id ? `Category ID ${data.category_id}` : "";
            tags = Array.isArray(data?.tags) ? data.tags : [];
            slug = data?.slug || String(topic_id);
          }
          const stream: any[] = Array.isArray(data?.post_stream?.posts) ? data.post_stream.posts : [];
          const sorted = stream.slice().sort((a, b) => (a.post_number || 0) - (b.post_number || 0));
          const filtered = sorted.filter((p) => (p.post_number || 0) >= current);
          for (const p of filtered) {
            if (fetchedPosts.length >= post_limit) break;
            fetchedPosts.push({
              number: p.post_number,
              username: p.username,
              created_at: p.created_at,
              content: (p.raw || p.cooked || p.excerpt || "").toString().slice(0, limit),
            });
          }
          if (filtered.length === 0) break; // no progress
          current = (filtered[filtered.length - 1]?.post_number || current) + 1;
        }
    
        const lines: string[] = [];
        lines.push(`# ${title}`);
        if (category) lines.push(category);
        if (tags.length) lines.push(`Tags: ${tags.join(", ")}`);
        lines.push("");
        for (const p of fetchedPosts) {
          lines.push(`- Post #${p.number} by @${p.username} (${p.created_at})`);
          lines.push(`  ${p.content}`);
        }
        lines.push("");
        lines.push(`Link: ${base}/t/${slug}/${topic_id}`);
        return { content: [{ type: "text", text: lines.join("\n") }] };
      } catch (e: any) {
        return { content: [{ type: "text", text: `Failed to read topic ${topic_id}: ${e?.message || String(e)}` }], isError: true };
      }
    }
  • Zod schema defining input parameters: topic_id (required positive integer), post_limit (optional 1-100), start_post_number (optional positive integer).
    const schema = z.object({
      topic_id: z.number().int().positive(),
      post_limit: z.number().int().min(1).max(100).optional(),
      start_post_number: z.number().int().min(1).optional().describe("Start from this post number (1-based)")
    });
  • Registers the 'discourse_read_topic' tool with the server, providing title, description, input schema, and handler function.
    export const registerReadTopic: RegisterFn = (server, ctx) => {
      const schema = z.object({
        topic_id: z.number().int().positive(),
        post_limit: z.number().int().min(1).max(100).optional(),
        start_post_number: z.number().int().min(1).optional().describe("Start from this post number (1-based)")
      });
    
      server.registerTool(
        "discourse_read_topic",
        {
          title: "Read Topic",
          description: "Read a topic metadata and first N posts.",
          inputSchema: schema.shape,
        },
        async ({ topic_id, post_limit = 5, start_post_number }, _extra: any) => {
          try {
            const { base, client } = ctx.siteState.ensureSelectedSite();
            const start = start_post_number ?? 1;
    
            // First request to load metadata/title and initial chunk
            let current = start;
            let fetchedPosts: Array<{ number: number; username: string; created_at: string; content: string }> = [];
            let slug = "";
            let title = `Topic ${topic_id}`;
            let category = "";
            let tags: string[] = [];
    
            const maxBatches = 10; // safety guard
            const limit = Number.isFinite(ctx.maxReadLength) ? ctx.maxReadLength : 50000;
            for (let i = 0; i < maxBatches && fetchedPosts.length < post_limit; i++) {
              // Ask for raw content when possible
              const url = current > 1 ? `/t/${topic_id}.json?post_number=${current}&include_raw=true` : `/t/${topic_id}.json?include_raw=true`;
              const data = (await client.get(url)) as any;
              if (i === 0) {
                title = data?.title || title;
                category = data?.category_id ? `Category ID ${data.category_id}` : "";
                tags = Array.isArray(data?.tags) ? data.tags : [];
                slug = data?.slug || String(topic_id);
              }
              const stream: any[] = Array.isArray(data?.post_stream?.posts) ? data.post_stream.posts : [];
              const sorted = stream.slice().sort((a, b) => (a.post_number || 0) - (b.post_number || 0));
              const filtered = sorted.filter((p) => (p.post_number || 0) >= current);
              for (const p of filtered) {
                if (fetchedPosts.length >= post_limit) break;
                fetchedPosts.push({
                  number: p.post_number,
                  username: p.username,
                  created_at: p.created_at,
                  content: (p.raw || p.cooked || p.excerpt || "").toString().slice(0, limit),
                });
              }
              if (filtered.length === 0) break; // no progress
              current = (filtered[filtered.length - 1]?.post_number || current) + 1;
            }
    
            const lines: string[] = [];
            lines.push(`# ${title}`);
            if (category) lines.push(category);
            if (tags.length) lines.push(`Tags: ${tags.join(", ")}`);
            lines.push("");
            for (const p of fetchedPosts) {
              lines.push(`- Post #${p.number} by @${p.username} (${p.created_at})`);
              lines.push(`  ${p.content}`);
            }
            lines.push("");
            lines.push(`Link: ${base}/t/${slug}/${topic_id}`);
            return { content: [{ type: "text", text: lines.join("\n") }] };
          } catch (e: any) {
            return { content: [{ type: "text", text: `Failed to read topic ${topic_id}: ${e?.message || String(e)}` }], isError: true };
          }
        }
      );
    };
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool reads data, implying it's a read-only operation, but doesn't cover aspects like authentication needs, rate limits, error handling, or what happens if parameters are invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise and front-loaded: 'Read a topic metadata and first N posts.' It uses a single, efficient sentence with no wasted words, making it easy to parse and understand the core purpose quickly. This is ideal for conciseness in tool descriptions.

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

Completeness2/5

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

Given the tool has no annotations, no output schema, and low schema description coverage (33%), the description is incomplete. It doesn't explain return values, error conditions, or behavioral nuances, leaving the agent with insufficient context to use the tool effectively. For a read operation with multiple parameters, more detail is needed to ensure proper usage.

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 description coverage is 33% (only 'start_post_number' has a description), so the description must compensate but adds minimal value. It mentions 'first N posts,' which loosely relates to 'post_limit,' but doesn't explain 'topic_id' or provide details beyond the schema. Since schema coverage is low, the description doesn't fully compensate, resulting in an adequate but incomplete parameter understanding.

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: 'Read a topic metadata and first N posts.' It specifies the verb ('Read') and resource ('topic metadata and first N posts'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'discourse_read_post' or 'discourse_filter_topics', which slightly limits its effectiveness in distinguishing use cases.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'discourse_read_post' (for individual posts) or 'discourse_filter_topics' (for topic lists), nor does it specify prerequisites or exclusions. This lack of context makes it harder for an agent to choose correctly among similar tools.

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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