cursorrules

Workspace rules that connect the coding agent to career-planning tools for job searches, resumes, and interviews.

In plain words
What is it for?
Finding specialized career advice, checking career readiness, scoring resumes for applicant-tracking systems, matching resumes to jobs, researching interview processes, and retrieving career roadmaps.
Why use it?
They tell the agent which career tasks it can support and which tool to use for each one, so career help is more targeted.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/karthikrshet/career-agents/cursorrules
Clone the repo
git clone --depth 1 https://github.com/karthikrshet/Career-Agents

Made for: Cursor.

Per session 254 This file is loaded in full into every session.
When invoked 254 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00254 $0.00254
Opus 5 $0.00127 $0.00127
Sonnet 5 $0.00051 $0.00051
Haiku 4.5 $0.00025 $0.00025

Measured 2d ago against content hash 4528032cf3cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cursorrules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

integrations/cursor/.cursorrules · 18 lines

What it actually says

Cursor Rules for Career-Agents MCP Integration

When working in this workspace, you have access to the Career-Agents MCP Server. Use the following tools to assist the user with career strategy, resume optimization, and interview preparation:

Available Tools & Guidelines

  • Agent Discovery: If the user is looking for specialized advice, use search_agents or recommend_agents to discover prompt instructions or relevant agents.
  • Career Assessment: Use career_assessment to audit the user's career preparedness.
  • Resume Auditing: Use resume_score to get an ATS compliance rating and find keyword gaps, or use job_match to compare a resume against a target job description.
  • Interview Preparation: Use company_track to lookup interview process details for target companies (e.g., Google, Stripe, Atlassian).
  • Roadmaps & Workflows: Use career_path or workflow_lookup to fetch step-by-step career milestones and repeatable operational workflows.

Sample Prompts

  • "Find the best Career-Agents for preparing for Atlassian SDE interviews."
  • "Score this resume: [resume text]"
  • "Show me the preparation roadmap for a frontend-engineer career path."
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 18 lines · 254 tokens per session scan A 4528032cf3cb

Subscribe to this mod's changes

cursorrules is a cursor rule published in the GitHub repository karthikrshet/Career-Agents (38 stars, last pushed 2d ago), licensed MIT. It adds 254 tokens to every session, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.