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get_latest_series

Retrieve the most recent data point for a U.S. labor statistics series from the Bureau of Labor Statistics API.

Instructions

Retrieve the most recent data point for a given BLS series ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYesBLS series ID, e.g. LAUCN040010000000005

Implementation Reference

  • Registration and handler definition for get_latest_series tool.
    server.tool(
      "get_latest_series",
      "Retrieve the most recent data point for a given BLS series ID.",
      {
        series_id: z
          .string()
          .regex(SERIES_ID_PATTERN, "Series ID must be uppercase with no special characters except _, -, #")
          .describe("BLS series ID, e.g. LAUCN040010000000005"),
      },
      async ({ series_id }) => {
        try {
          const data = await client.getLatestSeries(series_id);
          return { content: [{ type: "text" as const, text: JSON.stringify(data, null, 2) }] };
        } catch (error) {
          return wrapError(error);
        }
      }
    );
  • Implementation of the getLatestSeries method in the BLS API client.
    async getLatestSeries(seriesId: string): Promise<unknown> {
      try {
        const response = await this.http.get(
          `/timeseries/data/${seriesId}`,
          { params: { latest: true } }
        );
        return response.data;
      } catch (error) {
        this.handleError(error);
      }
    }
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 retrieves data (implying read-only), but doesn't mention potential constraints like rate limits, authentication needs, error handling, or data format. For a tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence that directly states the tool's function without any fluff. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what the returned data point includes (e.g., value, date, metadata), error scenarios, or how it integrates with sibling tools. For a data retrieval tool with rich context signals, this leaves too many gaps for effective agent use.

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?

The input schema has 100% description coverage, with the parameter 'series_id' well-documented in the schema (including pattern and example). The description adds no additional parameter semantics beyond implying it's for BLS data. Baseline 3 is appropriate since the schema does the heavy lifting.

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 ('Retrieve') and target ('most recent data point for a given BLS series ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_single_series' or 'get_multiple_series', which likely retrieve different scopes of data. This prevents 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?

No guidance is provided on when to use this tool versus alternatives. The description mentions retrieving the 'most recent' data point, but it doesn't clarify if this is for real-time updates, historical analysis, or how it differs from siblings like 'get_single_series' (which might retrieve all data points). This leaves the agent without context for tool selection.

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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