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getIngestJobRunStatus

Check the status of an ingestion job in SourceSync.ai to monitor data processing progress and verify completion.

Instructions

Checks the status of a previously submitted ingestion job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceIdNo
ingestJobRunIdYes
tenantIdNo

Implementation Reference

  • MCP tool handler that extracts parameters, creates a SourceSyncApiClient instance using createClient helper, and invokes the underlying getIngestJobRunStatus method.
    async (params) => {
      return safeApiCall(async () => {
        const { namespaceId, tenantId, ingestJobRunId } = params
    
        // Create a client with the provided API key
        const client = createClient({ namespaceId, tenantId })
    
        return await client.getIngestJobRunStatus({
          ingestJobRunId,
        })
      })
    },
  • src/index.ts:332-349 (registration)
    Registers the 'getIngestJobRunStatus' tool with the MCP server using server.tool, specifying name, description, input schema, and handler function.
    // Add getIngestJobRunStatus tool
    server.tool(
      'getIngestJobRunStatus',
      'Checks the status of a previously submitted ingestion job.',
      IngestJobRunStatusSchema.shape,
      async (params) => {
        return safeApiCall(async () => {
          const { namespaceId, tenantId, ingestJobRunId } = params
    
          // Create a client with the provided API key
          const client = createClient({ namespaceId, tenantId })
    
          return await client.getIngestJobRunStatus({
            ingestJobRunId,
          })
        })
      },
    )
  • Zod schema defining the input parameters for the getIngestJobRunStatus tool: optional namespaceId, required ingestJobRunId, optional tenantId.
    export const IngestJobRunStatusSchema = z.object({
      namespaceId: namespaceIdSchema.optional(),
      ingestJobRunId: z.string(),
      tenantId: tenantIdSchema,
    })
  • SourceSyncApiClient helper method that makes the HTTP GET request to the SourceSync API endpoint /v1/ingest-job-runs/{ingestJobRunId} with namespaceId query param to retrieve the job status.
    public async getIngestJobRunStatus({
      ingestJobRunId,
    }: Omit<
      SourceSyncGetIngestJobRunStatusRequest,
      'namespaceId'
    >): Promise<SourceSyncGetIngestJobRunStatusResponse> {
      return this.client
        .url(`/v1/ingest-job-runs/${ingestJobRunId}`)
        .query({ namespaceId: this.namespaceId })
        .get()
        .json<SourceSyncGetIngestJobRunStatusResponse>()
    }
  • TypeScript type definitions for the request (ingestJobRunId) and response (SourceSyncApiResponse<SourceSyncIngestJobRun>) used by the getIngestJobRunStatus API method.
    export type SourceSyncGetIngestJobRunStatusRequest = {
      ingestJobRunId: string
    }
    
    export type SourceSyncGetIngestJobRunStatusResponse =
      SourceSyncApiResponse<SourceSyncIngestJobRun>
Behavior2/5

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 checks status, which implies a read-only operation, but fails to detail critical aspects like authentication needs, rate limits, error handling, or what the status output entails (e.g., pending, completed, failed). This leaves significant gaps in understanding how the tool behaves.

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 a single, front-loaded sentence that efficiently conveys the core purpose without unnecessary words. Every part earns its place, making it highly concise and well-structured for quick understanding.

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's moderate complexity (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, parameter meanings, and expected outputs, failing to provide enough context for effective use by an AI agent. The conciseness does not compensate for these substantive gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'previously submitted ingestion job,' which hints at 'ingestJobRunId,' but does not explain the semantics of 'namespaceId' or 'tenantId,' or clarify that only 'ingestJobRunId' is required. This adds minimal value beyond the schema's structure.

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 action ('Checks the status') and resource ('a previously submitted ingestion job'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'ingestConnector' or 'ingestFile', which might involve status checks indirectly, so it falls short of a perfect score.

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 minimal guidance by implying usage after job submission ('previously submitted'), but it lacks explicit when-to-use instructions, alternatives (e.g., vs. 'fetchDocuments' for results), or prerequisites. No clear context for choosing this over other tools is given.

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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