本文へ移動
cccskills
無料GitHub で公開

onboarding

Initial environment setup. Browser, logins, DB, user data, profile, strategy.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seekerスター 58(GitHub 58 + cccskills 0)
連携ツールGmailLinkedIn

実行スコア 未検証

インストール方法を見る

含まれるファイル(1)

  • SKILL.md7.9 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Onboarding

Steps

Phase 1: Technical setup

  1. Verify node and npx

  2. .gitignore: .browser-profile/, .env, node_modules/

  3. npm init -y && npm install pg && npm install --save-dev @types/pg

  4. Ask user about browser visibility preference. Present these options and save the answer to preferences before opening any browser:

    • headless — Headless always. The agent works without showing the browser. Manual login/2FA remains headed (Gold Rule 5)
    • headed — Headed always. The user sees everything the agent does on screen
    • headed_logins_only — Headed only for logins/2FA, headless for everything else (default)
    • ask_each_time — The agent asks before each browser session whether the user wants to see it or not

    Save the preference:

    node scripts/db.js "INSERT INTO preferences (user_id, category, key, value, confidence, source) VALUES (<user_id>, 'tooling', 'browser_mode', '<chosen_value>', 1.0, 'explicit_statement') ON CONFLICT (user_id, category, key) DO UPDATE SET value = EXCLUDED.value, updated_at = NOW()" --write
    

    The agent must respect this preference in all flows that use the browser. Load it at every pre-flight:

    node scripts/db.js "SELECT value FROM preferences WHERE user_id = <user_id> AND category = 'tooling' AND key = 'browser_mode' AND status = 'active'"
    

    If no preference exists, default to headed_logins_only.

Phase 2: Browser and logins

  1. Open browser respecting the preference from step 4. For manual login it's always headed (Gold Rule 5). Use the wrapper (see AGENTS.md "Browser session"): node .agents/skills/browser-automation/scripts/browser.js open <url> --headed
  2. Ask for email. Navigate to provider login (Gmail → accounts.google.com, Outlook → outlook.live.com). Fill email with fill, click Next, wait for manual auth + 2FA
  3. Validate session: navigate to inbox, confirm URL doesn't redirect to login

Phase 3: Database setup

  1. Database setup. Neon is the default recommended option. Present the options in this order:

    • Option A (recommended): Create a free DB on Neon. The agent navigates to console.neon.tech, logs in with Google (reuses session), creates a "New project", names it job-seeker, selects nearest region, and reads the connection string (Show password + eval to extract)
    • Option B: Bring your own connection string. If the user already has a Postgres DB (Neon, Supabase, Railway, local, etc.), they paste the connection string directly

    Neon is presented as the default because it's free, serverless, and requires zero local setup. The agent should not wait for the user to ask about Neon, it should offer it proactively.

  2. Save connection string to .env as DATABASE_URL

  3. Ask for user's name

  4. Create users table and insert record via the db CLI (scripts/db.js):

    node scripts/db.js "CREATE TABLE IF NOT EXISTS users (id SERIAL PRIMARY KEY, name TEXT NOT NULL, email TEXT NOT NULL UNIQUE, data JSONB DEFAULT '{}')" --write
    node scripts/db.js "INSERT INTO users (name, email, data) VALUES ('<name>', '<email>', '{}'::jsonb) ON CONFLICT (email) DO UPDATE SET name = EXCLUDED.name" --write
    

Phase 4: LinkedIn

  1. Navigate to linkedin.com/login. Wait for manual auth + 2FA
  2. Validate session: navigate to linkedin.com/feed/
  3. Save LinkedIn profile URL to users.data.linkedin_profile via db CLI:
    node scripts/db.js "UPDATE users SET data = jsonb_set(data, '{linkedin_profile}', '\"<url>\"') WHERE id = <user_id>" --write
    
  4. Collect user info from all logged-in sites (LinkedIn, Gmail/Google): name, photo, phone, email. Save to users.data as JSONB via db CLI (jsonb_set). Useful for aligning profiles on other job platforms
  5. Check if profiles need updating (inconsistent data across sites). Report to user
  6. Close browser

Phase 5: Profile (CV-first)

  1. Ask for CV (URL or PDF). This is the first step of the profile flow (see profile skill, Step 1). The agent extracts experience, sector, profile, and infers career stage from the CV.
  2. Run the gap questionnaire (profile skill, Step 2). The agent generates only the questions the CV doesn't answer, adapted to the inferred career stage. Management questions only if applicable. No hardcoded deal-breakers.
  3. Ask about current situation and expectations (profile skill, Step 3). Employment status, urgency, salary, work mode, availability for interviews.

Phase 6: Strategy

  1. Define strategy (see strategy skill). Now that the agent has the full profile (CV + gaps + situation), it proposes a strategy level informed by everything above. Questions are adapted to the user's career stage:

    • If junior/mid: "Are you open to roles above your current level, or only same-level matches?"
    • If senior+ with management: "Would you accept IC roles or only Manager?"

    Save to DB:

    # Save level to preferences
    node scripts/db.js "INSERT INTO preferences (user_id, category, key, value, confidence, source) VALUES (<user_id>, 'workflow', 'strategy_level', '<level>', 1.0, 'explicit_statement') ON CONFLICT (user_id, category, key) DO UPDATE SET value = EXCLUDED.value, updated_at = NOW()" --write
    # Save detailed parameters to users.data.strategy
    node scripts/db.js "UPDATE users SET data = jsonb_set(data, '{strategy}', '<json>'::jsonb) WHERE id = <user_id>" --write
    

    The strategy JSON should contain all parameters (see AGENTS.md "Strategy levels" for the schema per level). If the user customizes any parameter, override the default for that level. If no strategy is set, default to selective.

Phase 7: Polish suggestion

  1. Suggest aligning CV and LinkedIn profile to the job target. After the strategy is defined, the agent compares the user's current CV and LinkedIn profile against the defined job target and identifies gaps (missing keywords, misaligned titles, underrepresented skills, weak LinkedIn headline). Present the analysis and offer to run the polish skill. If the user accepts, run polish. If not, remind them once at the end of onboarding.

Phase 8: Wrap up

  1. Voice and style capture (profile skill, voice phase). Infer tone and style from LinkedIn sent messages and Gmail sent emails. Confirm with user. Save to users.data.style_profile.
  2. Platform assignment (profile skill, platforms phase). Cross-reference profile vs PLATFORMS.md, assign tiers, save to users.data.platforms. Don't ask the user.
  3. Summary. Present a summary of everything that was set up: browser mode, DB, profile, strategy, polish status, platforms. One line per item.

Rules

  • Full autonomy. Only ask for intervention to: data that can't be inferred, manual login, 2FA
  • Email login first, LinkedIn second
  • Validate session after each login
  • .env not tracked
  • Custom schema: only create tables when needed
  • JSONB for semi-structured data in users.data
  • Single user (repo owner)
  • Browser mode preference is set in step 4 and stored in preferences table. All subsequent flows must load and respect it. Manual login/2FA is always headed regardless of preference (Gold Rule 5)
  • CV is requested before strategy. The profile (CV analysis + gap questionnaire + situation) informs the strategy questions. Never ask strategy questions before having the CV
  • Neon is the default DB option. Present it proactively as the recommended choice. Don't wait for the user to ask
  • Polish is suggested at the end of onboarding. After strategy is defined, the agent proactively suggests aligning the CV and LinkedIn profile to the job target. Never skip this step
  • Questions adapt to career stage. The agent infers career stage from the CV and adapts strategy questions accordingly. Never ask "IC or Manager?" to a junior

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

コメント

ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。

まだコメントはありません。最初のコメントを書いてみませんか。

送信するとすぐに公開されます。メールアドレスや電話番号などの個人情報は書かないでください。URL は 2 つまでです。

0 / 1000 文字

このフォームは reCAPTCHA で保護されており、Google のプライバシーポリシーと利用規約が適用されます。

同じリポジトリのスキル

apply

無料

Searches for jobs on LinkedIn, filters by profile Must-haves, applies via Easy Apply, registers each application in DB.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

Control a dedicated browser via agent-browser (Vercel). Use when automating web apps, scraping authenticated sites, filling forms, or navigating SPAs. Do NOT use for desktop apps or API-only integrations.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

daily

無料

Periodic routine that runs news, cleans up inbox and applies if there's no recent activity. Designed to run 1-2 times per day.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

dashboard

無料

Opens a local web dashboard that visualizes the job application pipeline, funnel stats, recent messages, and target company status. The agent opens it at the end of a round so the user can visually review the pipeline.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

db

無料

Safe Postgres CLI. Reads DATABASE_URL from .env, runs SQL, prints JSON. Read-only by default.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

memory

無料

Autonomous user preference detection, storage and injection. The agent detects preferences from conversation, saves them to Postgres, and loads active ones at the start of every flow.

日本語の概要は準備中です。原文の説明を表示しています。

galiprandi/job-seeker582026年10月26日 更新

galiprandi のスキルをすべて見る

このスキルの問題を報告する