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nteract/semiotic

by nteract
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reportIssue

Submit bug reports or feature requests for Semiotic data visualizations by generating pre-filled GitHub issue URLs with structured details.

Instructions

Generate a GitHub issue URL for Semiotic bug reports or feature requests. Returns a URL the user can open to submit. For rendering bugs, include the component name, props summary, and any diagnoseConfig output in the body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesIssue title, e.g. 'Bug: BarChart tooltip shows undefined'
bodyNoIssue body with details, reproduction steps, diagnoseConfig output
labelsNoGitHub labels, e.g. ['bug'] or 'bug'

Implementation Reference

  • ai/mcp-server.ts:366-390 (handler)
    The handler function `reportIssueHandler` which constructs the GitHub issue URL based on provided title, body, and labels.
    async function reportIssueHandler(args: { title?: string; body?: string; labels?: string[] | string }): Promise<ToolResult> {
  const title = args.title
  const body = args.body
  const labels = args.labels

  if (!title) {
    return {
      content: [{ type: "text" as const, text: "Missing 'title' field. Provide { title: 'Bug: ...', body: '...', labels?: ['bug'] }." }],
      isError: true,
    }
  }

  const params = new URLSearchParams()
  params.set("title", title)
  if (body) params.set("body", body)
  if (labels) {
    const labelList = Array.isArray(labels) ? labels.join(",") : labels
    params.set("labels", labelList)
  }

  const url = `https://github.com/${REPO}/issues/new?${params.toString()}`
  return {
    content: [{ type: "text" as const, text: `Open this URL to submit the issue:\n\n${url}` }],
  }
}
  • ai/mcp-server.ts:440-449 (registration)
    Registration of the `reportIssue` tool within the McpServer using Zod schemas for validation.
    srv.tool(
  "reportIssue",
  "Generate a GitHub issue URL for Semiotic bug reports or feature requests. Returns a URL the user can open to submit. For rendering bugs, include the component name, props summary, and any diagnoseConfig output in the body.",
  {
    title: z.string().describe("Issue title, e.g. 'Bug: BarChart tooltip shows undefined'"),
    body: z.string().optional().describe("Issue body with details, reproduction steps, diagnoseConfig output"),
    labels: z.union([z.array(z.string()), z.string()]).optional().describe("GitHub labels, e.g. ['bug'] or 'bug'"),
  },
  reportIssueHandler
)
  • ai/mcp-server.ts:443-449 (schema)
    Zod schema defining the input arguments (title, body, labels) for the `reportIssue` tool.
      {
    title: z.string().describe("Issue title, e.g. 'Bug: BarChart tooltip shows undefined'"),
    body: z.string().optional().describe("Issue body with details, reproduction steps, diagnoseConfig output"),
    labels: z.union([z.array(z.string()), z.string()]).optional().describe("GitHub labels, e.g. ['bug'] or 'bug'"),
  },
  reportIssueHandler
)

Tool Definition Quality

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates a URL and returns it to the user, which implies a read-only operation that doesn't modify data. However, it doesn't mention authentication requirements, rate limits, or what happens if the GitHub repository is inaccessible. The description adds some context about what to include in the body for rendering bugs, but lacks comprehensive behavioral details.

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 perfectly concise and well-structured in two sentences. The first sentence states the core purpose and return value. The second sentence provides specific usage guidance for a common scenario. Every word earns its place with zero wasted text.

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?

For a tool with 3 parameters, 100% schema coverage, and no output schema, the description is reasonably complete. It explains what the tool does, when to use it, and provides specific guidance for rendering bugs. The main gap is the lack of output information - while it mentions 'Returns a URL,' it doesn't describe the URL format or what happens if generation fails. Given the good schema coverage, this is mostly adequate.

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 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema: it mentions that the body should include 'component name, props summary, and any diagnoseConfig output' for rendering bugs, which provides some semantic context for the body parameter. However, it doesn't add significant meaning beyond what's already in the schema descriptions.

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 a GitHub issue URL for Semiotic bug reports or feature requests.' It specifies the exact action (generate URL) and resource (GitHub issue), and distinguishes it from sibling tools like diagnoseConfig or renderChart by focusing on issue reporting rather than diagnostics or rendering.

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 clear context for when to use this tool: 'For Semiotic bug reports or feature requests.' It gives specific guidance for rendering bugs: 'include the component name, props summary, and any diagnoseConfig output in the body.' However, it doesn't explicitly state when NOT to use it or name alternatives among sibling 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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