HireJack

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Get Market History

get_market_history

Read-only

Analyze hiring market trends over time with daily or monthly data on job counts, remote share, compensation, and skill distributions.

Instructions

Time-series of market-wide hiring stats: total jobs, remote share, compensation, seniority + family distribution, top skills. Analyst tier. Daily resolution back to early March 2026; monthly resolution from March 2026. Use for 'how has the market shifted in 2026?' or 'is remote hiring trending up?'. Not for the current snapshot — use get_market_pulse for that.

Input Schema

TableJSON Schema

Name	Required	Description
`days`	No	Days of daily history (1-90, default 30). Only used when range='daily'; ignored for range='monthly'.
`range`	No	Granularity. 'daily' returns up to 90 days back (rich, recent). 'monthly' returns up to 24 months back (coarser, longer view). Defaults to daily.
`detail`	No	'compact' (default) returns a slim per-snapshot series (date, jobs, companies, remote share, median comp) plus full distributions for only the first and latest snapshots — enough for trend analysis at ~10x less output. 'full' returns every snapshot's complete distributions (seniority, family, top skills); only use when you need per-date distribution detail.
`months`	No	Months of monthly history (1-24, default 12). Only used when range='monthly'; ignored for range='daily'.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	Market-wide hiring time-series; shape depends on `detail` (compact: series+endpoints, full: snapshots)
`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.

Changed3 schema fields changedv0.3.5Jul 17, 2026

changedInput schema / properties / days / description

Previous value: -"Days of daily history (default 30, max 90; only used when range=daily)"New value: +"Days of daily history (1-90, default 30). Only used when range='daily'; ignored for range='monthly'."

changedInput schema / properties / months / description

Previous value: -"Months of monthly history (default 12; only used when range=monthly)"New value: +"Months of monthly history (1-24, default 12). Only used when range='monthly'; ignored for range='daily'."

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": "Market-wide hiring time-series; shape depends on `detail` (compact: series+endpoints, full: snapshots)",
+      "properties": {
+        "days": {
+          "description": "Window size (daily granularity)",
+          "type": "number"
+        },
+        "detail": {
+          "description": "'compact' — present only in compact mode",
+          "type": "string"
+        },
+        "endpoints": {
+          "additionalProperties": true,
+          "description": "Compact mode: full distributions for the first and latest snapshots only",
+          "properties": {
+            "first": {
+              "additionalProperties": true,
+              "properties": {
+                "compensationStats": {
+                  "additionalProperties": true,
+                  "description": "Salary stats incl. marketMedian (annual USD)",
+                  "properties": {},
+                  "type": "object"
+                },
+                "date": {
+                  "description": "YYYY-MM-DD (daily granularity)",
+                  "type": "string"
+                },
+                "familyDistribution": {
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "month": {
+                  "description": "YYYY-MM (monthly granularity)",
+                  "type": "string"
+                },
+                "remoteDistribution": {
+                  "additionalProperties": true,
+                  "description": "Job counts by work mode (remote/hybrid/onsite)",
+                  "properties": {},
+                  "type": "object"
+                },
+                "seniorityDistribution": {
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "topSkills": {
+                  "description": "Top 10 skills by prevalence",
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "totals": {
+                  "additionalProperties": true,
+                  "description": "Market totals (jobs, companies, engineeringPct, ...)",
+                  "properties": {},
+                  "type": "object"
+                }
+              },
+              "type": "object"
+            },
+            "latest": {
+              "additionalProperties": true,
+              "properties": {
+                "compensationStats": {
+                  "additionalProperties": true,
+                  "description": "Salary stats incl. marketMedian (annual USD)",
+                  "properties": {},
+                  "type": "object"
+                },
+                "date": {
+                  "description": "YYYY-MM-DD (daily granularity)",
+                  "type": "string"
+                },
+                "familyDistribution": {
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "month": {
+                  "description": "YYYY-MM (monthly granularity)",
+                  "type": "string"
+                },
+                "remoteDistribution": {
+                  "additionalProperties": true,
+                  "description": "Job counts by work mode (remote/hybrid/onsite)",
+                  "properties": {},
+                  "type": "object"
+                },
+                "seniorityDistribution": {
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "topSkills": {
+                  "description": "Top 10 skills by prevalence",
+                  "items": {
+                    "additionalProperties": true,
+                    "properties": {},
+                    "type": "object"
+                  },
+                  "type": "array"
+                },
+                "totals": {
+                  "additionalProperties": true,
+                  "description": "Market totals (jobs, companies, engineeringPct, ...)",
+                  "properties": {},
+                  "type": "object"
+                }
+              },
+              "type": "object"
+            }
+          },
+          "type": "object"
+        },
+        "granularity": {
+          "description": "'daily' | 'monthly'",
+          "type": "string"
+        },
+        "months": {
+          "description": "Window size (monthly granularity)",
+          "type": "number"
+        },
+        "series": {
+          "description": "Compact mode: slim per-snapshot series, oldest first",
+          "items": {
+            "additionalProperties": true,
+            "properties": {
+              "companies": {
+                "description": "Total tracked companies",
+                "type": "number"
+              },
+              "date": {
+                "description": "YYYY-MM-DD (daily granularity)",
+                "type": "string"
+              },
+              "engineeringPct": {
+                "description": "Engineering share of jobs, 0-100",
+                "type": "number"
+              },
+              "jobs": {
+                "description": "Total tracked jobs",
+                "type": "number"
+              },
+              "medianComp": {
+                "description": "Market median salary, annual USD",
+                "type": "number"
+              },
+              "month": {
+                "description": "YYYY-MM (monthly granularity)",
+                "type": "string"
+              },
+              "remotePct": {
+                "description": "Remote share of jobs, 0-100; null when work-mode data is missing",
+                "nullable": true,
+                "type": "number"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "snapshots": {
+          "description": "Full mode (detail='full'): every snapshot's complete distributions, oldest first",
+          "items": {
+            "additionalProperties": true,
+            "properties": {
+              "compensationStats": {
+                "additionalProperties": true,
+                "description": "Salary stats incl. marketMedian (annual USD)",
+                "properties": {},
+                "type": "object"
+              },
+              "date": {
+                "description": "YYYY-MM-DD (daily granularity)",
+                "type": "string"
+              },
+              "familyDistribution": {
+                "items": {
+                  "additionalProperties": true,
+                  "properties": {},
+                  "type": "object"
+                },
+                "type": "array"
+              },
+              "month": {
+                "description": "YYYY-MM (monthly granularity)",
+                "type": "string"
+              },
+              "remoteDistribution": {
+                "additionalProperties": true,
+                "description": "Job counts by work mode (remote/hybrid/onsite)",
+                "properties": {},
+                "type": "object"
+              },
+              "seniorityDistribution": {
+                "items": {
+                  "additionalProperties": true,
+                  "properties": {},
+                  "type": "object"
+                },
+                "type": "array"
+              },
+              "topSkills": {
+                "description": "Top 10 skills by prevalence",
+                "items": {
+                  "additionalProperties": true,
+                  "properties": {},
+                  "type": "object"
+                },
+                "type": "array"
+              },
+              "totals": {
+                "additionalProperties": true,
+                "description": "Market totals (jobs, companies, engineeringPct, ...)",
+                "properties": {},
+                "type": "object"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "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

A4.9/5.0

Behavior5/5

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

Annotations declare readOnlyHint=true, confirming safe read operation. Description adds behavioral details like data resolution (daily back to early March 2026, monthly from March 2026) and explains the difference between compact and full detail modes. 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.

Conciseness5/5

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

Three sentences, front-loaded with the core purpose and key outputs. Every sentence adds essential information without waste.

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 the tool's complexity (4 parameters, two granularities, two detail modes), the description covers resolution, parameter interactions, and distinguishes from sibling tools. Output schema exists, so return values need not be detailed.

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?

Schema already provides 100% coverage with detailed parameter descriptions. The description adds value by explaining when parameters are used or ignored based on other parameters (e.g., days ignored when range=monthly), which aids correct usage.

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 clearly states it returns time-series of market-wide hiring stats with specific metrics (total jobs, remote share, compensation, etc.). It distinguishes from siblings like get_market_pulse by explicitly noting it is not for current snapshots.

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 provides usage scenarios: 'how has the market shifted in 2026?' or 'is remote hiring trending up?'. Also clearly states when not to use: for current snapshot, use get_market_pulse instead.

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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