# When Tracking Dual Career Intelligence Use Career Intel > When Tracking Dual Career Intelligence Use Career Intel - Skill: `dnyoussef/when-tracking-dual-career-intelligence-use-career-intel` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add dnyoussef/when-tracking-dual-career-intelligence-use-career-intel` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/when-tracking-dual-career-intelligence-use-career-intel/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/when-tracking-dual-career-intelligence-use-career-intel --- /*============================================================================*/ /* SKILL SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: skill version: 1.0.0 description: | [assert|neutral] Automated US/EU career opportunity tracking with policy monitoring, EV-based ranking, and tailored application materials [ground:given] [conf:0.95] [state:confirmed] category: career-orchestration tags: - general author: system cognitive_frame: primary: evidential goal_analysis: first_order: "Execute skill workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic career-orchestration processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "skill", category: "career-orchestration", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Evidential", source: "Turkish", force: "How do you know?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["skill", "career-orchestration", "workflow"], context: "user needs skill capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Dual-Track Career Intelligence ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. Automated tracking of internal/external roles across US/EU markets with policy monitoring, visa leverage analysis, and tailored pitch generation. ## Overview This skill orchestrates 3 specialist agents to: 1. **Scout** (researcher) - Crawl job boards and normalize opportunities 2. **RegWatch** (researcher) - Diff EU policy/regulatory pages for visa changes 3. **Ranker** (analyst) - Score opportunities by Fit, Option Value, Speed, Cred Stack 4. **PitchPrep** (coder) - Generate tailored bullets, Q&A, and anecdotes **Critical differentiator**: Tracks visa leverage and immigration policy changes alongside traditional job factors. ## When to Use - **Weekly/bi-weekly**: Systematic career opportunity scanning - **Before major applications**: Generate tailored pitch materials - **EU policy changes**: Understand immigration implications - **Strategic planning**: Maintain optionality across geographies ## Assigned Agents ### Primary Agents **researcher (Scout role)** - Phase 1: Web scraping, data normalization, source aggregation - Expertise: API integration, data extraction, YAML processing - Tools: curl, jq, yq, bash scripting - Output: Raw CSV of opportunities with metadata **researcher (RegWatch role)** - Phase 2: Policy diff analysis, regulatory monitoring - Expertise: Document comparison, policy interpretation, change detection - Tools: diff, git, web scraping - Output: Policy change summary with action items ### Secondary Agents **analyst (Ranker role)** - Phase 3: Multi-factor scoring, EV calculation - Expertise: Scoring algorithms, decision analysis, prioritization - Tools: Python/Node scoring scripts, statistical analysis - Output: Ranked opportunities with justifications **coder (PitchPrep role)** - Phase 4: Content generation, tailoring, formatting - Expertise: Natural language generation, resume optimization, storytelling - Tools: Template engines, GPT-assisted writing, markdown formatting - Output: Tailored cover letters, Q&A prep, cred stack mapping ## Coordination Pattern ``` SKILL: dual-track-career-intelligence ↓ hierarchical-coordinator spawns 4 sequential phases ↓ Phase 1: Scout (researcher) → raw data Phase 2: RegWatch (researcher) → policy deltas Phase 3: Ranker (analyst) → scored opportunities Phase 4: PitchPrep (coder) → tailored materials ↓ All phases coordinate via Memory MCP with WHO/WHEN/PROJECT/WHY tagging ``` --- ## Phase 1: Scout (Data Collection) **Agent**: `researcher` (Scout role) ### Inputs - `data/sources/job_boards.yml` - Job board APIs and search parameters - `data/profiles/cv_core.md` - Keywords and skills to match ### Commands Executed ```bash #!/bin/bash # Phase 1: Job Board Scanning # PRE-TASK HOOK npx claude-flow@alpha hooks pre-task \ --description "Career intel: job board scanning" \ --agent "researcher" \ --role "Scout" \ --skill "dual-track-career-intelligence" # SESSION RESTORE (if resuming) npx claude-flow@alpha hooks session-restore \ --session-id "career-intel-$(date +%Y-%W)" # SETUP WEEK=$(date +%Y-%W) mkdir -p outputs/reports mkdir -p raw_data # READ CONFIG BOARDS=$(yq eval '.boards[].url' data/sources/job_boards.yml) KEYWORDS=$(yq eval '.search_keywords | join(",")' data/sources/job_boards.yml) GEO=$(yq eval '.geo_filters | join(",")' data/sources/job_boards.yml) # SCRAPE JOB BOARDS echo "title,company,location,url,posted_date,visa_support,remote_ok,comp_signal" > raw_data/jobs_${WEEK}.csv for BOARD in $BOARDS; do echo "[Scout] Scanning: $BOARD" # Example API call (adapt to actual board APIs) curl -s "${BOARD}/api/jobs?keywords=${KEYWORDS}&geo=${GEO}" \ | jq -r '.results[] | [ .title, .company, .location, .apply_url, .posted_date, .visa_sponsorship, .remote_allowed, (.salary.min // 0) ] | @csv' \ >> raw_data/jobs_${WEEK}.csv sleep 2 # Rate l /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/career-orchestration/skill/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "skill-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] SKILL_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]