RocketList

by ai.rocketlist

Overview Discussions Admin

Search jobs

search_jobs

Read-onlyIdempotent

Search public active Rocketlist jobs. Returns bounded, non-personal job data only.

All list arguments are arrays of strings; passing a bare string is a validation error.

Filters:

query: free-text over job title, company, location and category. Matched as prefix tokens, so 'engineer' also matches 'Engineering'.
skills: matched against the job's listed tech stack.
domain: exact company industry/vertical, e.g. ['Fintech'].
city: substring of the job's city or country.
remote_only: keep only remote roles.
investor: companies backed by these investors, e.g. ['Index Ventures']. Common aliases resolve ('a16z' finds Andreessen Horowitz). Populated for about 83% of hiring companies, so a company with no recorded investors is never returned when this is set.
stage: exact company funding stage from ['Pre-Seed', 'Seed', 'Series A', 'Series B', 'Series C', 'Series D', 'Series D+', 'Series E', 'Series F', 'Series G', 'Growth', 'Public', 'Acquired', 'Bootstrapped'], case-insensitive. About 12% of hiring companies have no stage recorded and are excluded when this is set.
min_experience_years / max_experience_years: bounds on the years of experience the role requires at minimum. max_experience_years=5 means 'requires 5 years or fewer'. Only about 56% of jobs state a requirement; the rest are excluded when either bound is set.
yc_batch: Y Combinator batches, e.g. ['F26'] or ['Fall 2026'] (W/X/S/F + year). Covers the batches in the reviewed cohort list (currently YC Fall 2026).
founder_origin: countries the founders come from (where they grew up or studied), by name or ISO code, e.g. ['Germany'] or ['DE']. Company-level, reviewed for the same cohorts as yc_batch; a company matches if any founder does.
near: a place, as an address, a street corner ('3rd and Folsom, San Francisco') or 'lat,lng'. Keeps companies whose office (the reviewed street address on getedge.cc/map) is within radius_m metres (default 1000) or walk_minutes on foot (64 m of straight line per minute). Results carry office_address, distance_m and walk_minutes, nearest first.
radius_m / walk_minutes: size of the near area; give one.

Input Schema

Name	Required	Description	Default
`city`	No
`near`	No
`limit`	No
`query`	No
`stage`	No
`domain`	No
`skills`	No
`investor`	No
`radius_m`	No
`yc_batch`	No
`remote_only`	No
`walk_minutes`	No
`founder_origin`	No
`max_experience_years`	No
`min_experience_years`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedOct 23, 2026

addedInput schema / properties / founder_origin

Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Founder Origin"
+}

addedInput schema / properties / near

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Near"
+}

addedInput schema / properties / radius_m

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Radius M"
+}

addedInput schema / properties / walk_minutes

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Walk Minutes"
+}

addedInput schema / properties / yc_batch

Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Yc Batch"
+}

First observedSep 21, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already cover the read-only, idempotent, non-destructive profile, and the description goes well beyond them: it warns that bare-string list arguments are a validation error, and discloses data-coverage exclusions (investor populated ~83%, stage ~12% missing, experience stated ~56%) so the agent knows filters silently drop jobs. It also states the near results are ordered nearest-first and carry office_address, distance_m and walk_minutes.

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?

Front-loaded with scope, then a compact bulleted filter list where each entry earns its place — the coverage percentages and aliasing notes are the kind of detail an agent cannot get elsewhere. It runs long, but padding is minimal; the only dead weight is the unexplained omission of limit alongside verbose percent phrasings.

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?

Fifteen optional parameters with no schema descriptions demand heavy prose, and the description delivers for nearly all of them; return shape is covered by the output schema. Missing pieces are minor: no mention of limit/pagination behavior or what a result set's overall shape is when near is not set.

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

Parameters5/5

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

Schema coverage is 0%, so the description carries the full burden and does it: prefix-token matching for query ('engineer' matches 'Engineering'), skills vs domain semantics, investor alias resolution ('a16z'), the exact stage enumeration, and the counterintuitive reading of max_experience_years='requires 5 years or fewer'. Only limit goes undocumented.

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?

Opening line names a specific verb and resource ('Search public active Rocketlist jobs') and immediately scopes the corpus ('bounded, non-personal job data only'), which separates it from get_job and search_companies without the reader needing either schema.

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

Usage Guidelines3/5

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

The bullet list explains how each filter behaves, which strongly implies how to compose a query, but it never states when to use this tool rather than search_companies or get_job, and gives no explicit exclusions or prerequisite conditions. Usage is inferable rather than stated.

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

All RocketList tools Inspect

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