DNYoussef /============================================================================/ /* 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:
- Scout (researcher) - Crawl job boards and normalize opportunities
- RegWatch (researcher) - Diff EU policy/regulatory pages for visa changes
- Ranker (analyst) - Score opportunities by Fit, Option Value, Speed, Cred Stack
- 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 parametersdata/profiles/cv_core.md- Keywords and skills to match
Commands Executed
#!/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] <promise>SKILL_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]