Skip to main content
Glama

CareerProof MCP

by ai.careerproof.mcp
OverviewDiscussionsAdmin

careerproof_task_result

Read-onlyIdempotent

Retrieve the full result of a completed async task. Call careerproof_task_status first to confirm status='completed'. The resource_id varies by result_type: 'analysis' needs analysis_id (from atlas_start_gem_analysis), 'batch_gem' needs job_id (from atlas_start_batch_gem), 'report' needs report_id (from atlas_start_report), 'custom_eval_inference' needs model_id, 'custom_eval_batch' needs batch_id, 'dialogue_assessment' needs session_id. 'jd_fit_batch' requires context_id instead of resource_id. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesThe task_id of a completed async task
batch_idNoFor result_type='jd_fit_batch': scope results to a specific batch (from atlas_start_jd_fit_batch). Strongly recommended — eliminates duplicates from historical runs in the same context.
context_idNoContext ID (required for 'jd_fit_batch' results, from atlas_list_contexts)
resource_idNoResource-specific ID: analysis_id for 'analysis'/'fit_match'/'fit_rank', job_id for 'batch_gem', report_id for 'report', model_id for 'custom_eval_inference', batch_id for 'custom_eval_batch', session_id for 'dialogue_assessment'
result_typeYesType of result to fetch (determines the backend endpoint used)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / batch_id
      Added value: +{
+  "description": "For result_type='jd_fit_batch': scope results to a specific batch (from atlas_start_jd_fit_batch). Strongly recommended — eliminates duplicates from historical runs in the same context.",
+  "type": "number"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already state readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context: the prerequisite status check, the varying resource_id mapping, and the special jd_fit_batch case requiring context_id instead of resource_id. No contradictions.

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 front-loaded with the main purpose and prerequisite. It is somewhat lengthy due to the detailed mapping, but every sentence adds value. No redundancy.

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 5 parameters and multiple enum values, the description covers the prerequisite, resource mapping, special cases, and deduplication hint. Lacks details on return format (no output schema), but the complexity of responses likely varies by type, so explicit return format might be excessive.

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

Parameters4/5

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

The input schema has 100% description coverage, so parameters are already documented. The description adds value by explaining the mapping between resource_id and result_type, and by noting that jd_fit_batch uses context_id instead of resource_id. It also suggests batch_id for deduplication, which is beyond the schema.

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 starts with 'Retrieve the full result of a completed async task,' which clearly states the verb and resource. It distinguishes from sibling careerproof_task_status by specifying that this tool is for completed tasks only, and the resource_id mapping differentiates it from other get tools that target specific result types directly.

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?

It explicitly advises to call careerproof_task_status first to confirm status='completed'. The mapping of resource_id to result_type provides clear context for each use case. It does not explicitly list when not to use this tool vs. alternatives like atlas_get_analysis, but the prerequisite and parameter guidance are strong.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All CareerProof MCP toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources