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G-Hensley
by G-Hensley

Get Job Opportunities

get_job_opportunities

Retrieve recently discovered job opportunities from automated monitoring. Filter by resume cluster and limit the number of results.

Instructions

Get recently discovered job opportunities from automated monitoring

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clusterNoFilter by resume cluster (full-stack-react, frontend-react, nextjs-focused, general-swe)
limitNoMaximum number of jobs to return

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes

Implementation Reference

  • Handler for get_job_opportunities: reads latest.json from GitHub, optionally filters by cluster and limits results, returns JSON string or error message.
      async ({ cluster, limit }) => {
        try {
          const opportunities = await readJsonFile<JobOpportunitiesData>("job-applications/opportunities/latest.json");
          let jobs = opportunities.jobs || [];
          if (cluster) {
            jobs = jobs.filter(j => j.cluster === cluster);
          }
          if (limit) {
            jobs = jobs.slice(0, limit);
          }
          return { content: [{ type: "text", text: JSON.stringify(jobs, null, 2) }] };
        } catch {
          return { content: [{ type: "text", text: "No job opportunities file found." }] };
        }
      }
    );
  • api/mcp.ts:307-333 (registration)
    Registration of the get_job_opportunities tool with input schema (cluster, limit) and output schema.
    server.registerTool(
      "get_job_opportunities",
      {
        title: "Get Job Opportunities",
        description: "Get recently discovered job opportunities from automated monitoring",
        inputSchema: {
          cluster: z.string().optional().describe("Filter by resume cluster (full-stack-react, frontend-react, nextjs-focused, general-swe)"),
          limit: z.number().optional().describe("Maximum number of jobs to return"),
        },
        outputSchema: textContentOutputSchema,
      },
      async ({ cluster, limit }) => {
        try {
          const opportunities = await readJsonFile<JobOpportunitiesData>("job-applications/opportunities/latest.json");
          let jobs = opportunities.jobs || [];
          if (cluster) {
            jobs = jobs.filter(j => j.cluster === cluster);
          }
          if (limit) {
            jobs = jobs.slice(0, limit);
          }
          return { content: [{ type: "text", text: JSON.stringify(jobs, null, 2) }] };
        } catch {
          return { content: [{ type: "text", text: "No job opportunities file found." }] };
        }
      }
    );
  • Type definitions for JobOpportunity and JobOpportunitiesData used by the tool handler.
    export interface JobOpportunity {
      title: string;
      company: string;
      location: string;
      url: string;
      cluster?: string;
      resume?: string;
      salary_min?: number;
      salary_max?: number;
      posted_date?: string;
    }
    
    export interface JobOpportunitiesData {
      generated_at: string;
      jobs: JobOpportunity[];
    }
  • Helper that fetches JSON from GitHub and parses it. Used by the handler to read job opportunities data.
    async function readJsonFile<T>(relativePath: string): Promise<T> {
      const content = await fetchFromGitHub(relativePath);
      return JSON.parse(content) as T;
    }
  • Common output schema for text content, referenced by the tool's outputSchema.
    const textContentOutputSchema = z.object({
      content: z.array(
        z.object({
          type: z.literal("text"),
          text: z.string(),
        })
      ),
    });
Behavior2/5

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

No annotations exist, so the description should disclose behavioral traits. It only mentions 'recently discovered' and 'automated monitoring', but omits details like whether the operation is read-only, any side effects, rate limits, or data freshness. Given the lack of annotations, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no extraneous words. It is efficient but could benefit from slightly more context without becoming verbose.

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?

An output schema exists (not shown but indicated), so return values are covered. However, the description lacks details on data source, update frequency, and the exact definition of 'recently'. For a tool with two parameters and a simple purpose, it is adequate but not fully complete.

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 has 100% description coverage for both parameters ('cluster' and 'limit'). The tool description does not add extra meaning beyond the schema, so it scores the baseline of 3. It explains neither the purpose of clustering nor how the limit affects results.

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 retrieves 'recently discovered job opportunities from automated monitoring'. It uses a specific verb ('Get') and a distinct resource ('job opportunities'), differentiating it from sibling tools like 'get_job_applications' or 'get_interviews'. However, 'recently' is somewhat vague and could be more precise.

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 does not mention prerequisites, context, or when not to use it. With numerous sibling tools, explicit usage guidance is lacking.

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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