HireJack

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Market Position

market_position

Read-only

Evaluate your market position score based on skill demand, seniority, and remote availability. Get salary benchmarks and top companies matching your skills.

Instructions

Compute the authenticated user's market position score (0-100). Pro tier. Weighted: 50% skill demand against current market, 20% seniority fit, 15% remote availability for the user's preference, 15% skill breadth. Returns score, matchingJobs count, salaryMedian for matching roles, per-skill demand breakdown, and the top companies whose tech stacks align best with the user's skills. Use for queries like 'how do I stack up against the market?' or 'what's my market position right now?'. Not for job-specific (match_job) or company-specific (company_fit) scores.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	The authenticated user's overall market position
`meta`	No	Request/response metadata (pagination cursors, snapshot timestamps, applied filters)
`citation_url`	No	hirejack.com URL to cite when surfacing this result

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.5Jul 17, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "citation_url": {
+      "description": "hirejack.com URL to cite when surfacing this result",
+      "type": "string"
+    },
+    "data": {
+      "additionalProperties": true,
+      "description": "The authenticated user's overall market position",
+      "properties": {
+        "matchingJobs": {
+          "description": "Conservative estimate of jobs matching the user's top skills",
+          "type": "number"
+        },
+        "message": {
+          "description": "Present (with score 0) when the profile has no skills or market data is unavailable",
+          "type": "string"
+        },
+        "remoteAvailPct": {
+          "description": "Share of jobs that are remote or hybrid, 0-100",
+          "type": "number"
+        },
+        "salaryMedian": {
+          "description": "Market median salary, annual USD",
+          "type": "number"
+        },
+        "score": {
+          "description": "Market position score, 0-100 (skill demand 50%, seniority fit 20%, remote availability 15%, skill breadth 15%)",
+          "type": "number"
+        },
+        "seniorityJobPct": {
+          "description": "Share of jobs at the user's seniority level, 0-100",
+          "type": "number"
+        },
+        "skillDemand": {
+          "description": "Per-skill market demand for each of the user's skills, highest demand first",
+          "items": {
+            "additionalProperties": true,
+            "properties": {
+              "companies": {
+                "description": "Companies mentioning the skill",
+                "type": "number"
+              },
+              "companyPct": {
+                "description": "Share of tracked companies mentioning it, 0-100",
+                "type": "number"
+              },
+              "demand": {
+                "description": "'high' | 'medium' | 'low' | 'niche'",
+                "type": "string"
+              },
+              "rank": {
+                "description": "Rank among top market skills; null when not ranked",
+                "nullable": true,
+                "type": "number"
+              },
+              "skill": {
+                "type": "string"
+              },
+              "totalMentions": {
+                "description": "Job postings mentioning it",
+                "type": "number"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "topMatchingCompanies": {
+          "description": "Companies whose tech stacks best overlap the user's skills (capped at 10)",
+          "items": {
+            "additionalProperties": true,
+            "properties": {
+              "domain": {
+                "description": "Pass to get_company_profile / company_fit",
+                "type": "string"
+              },
+              "matchingSkills": {
+                "description": "How many of the user's skills appear in the company's top skills",
+                "type": "number"
+              },
+              "name": {
+                "type": "string"
+              },
+              "skills": {
+                "description": "The overlapping skill names (capped at 5)",
+                "items": {
+                  "type": "string"
+                },
+                "type": "array"
+              },
+              "totalJobs": {
+                "type": "number"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "totals": {
+          "additionalProperties": true,
+          "properties": {
+            "trackedCompanies": {
+              "type": "number"
+            },
+            "trackedJobs": {
+              "type": "number"
+            },
+            "userSkillCount": {
+              "type": "number"
+            }
+          },
+          "type": "object"
+        }
+      },
+      "type": "object"
+    },
+    "meta": {
+      "additionalProperties": true,
+      "description": "Request/response metadata (pagination cursors, snapshot timestamps, applied filters)",
+      "properties": {},
+      "type": "object"
+    }
+  },
+  "required": [
+    "data"
+  ],
+  "type": "object"
+}

First observedv0.1.6Jul 11, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations indicate readOnlyHint=true; description adds detailed computation weighting (50% skill demand, etc.) and expected output fields. Does not disclose rate limits or authentication beyond 'Pro tier', but is largely transparent.

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?

Description is concise and front-loaded with purpose and weighting, though the weight breakdown could be slightly more succinct. No unnecessary repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and presence of an output schema, the description fully covers tool functionality, including inputs (none), computation logic, and return fields. Appropriate for its complexity.

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?

No parameters; schema coverage is 100%. Description explains the computation context, which is sufficient for a param-less tool. Baseline score of 4 applies.

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?

Clearly states it computes a market position score (0-100) with weighted breakdown. Distinguishes from job-specific and company-specific tools, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly lists example queries and what the tool is not for (job-specific or company-specific scores), providing clear guidance on when to use vs. alternatives.

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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