job-scout

job-scout is a skill for Claude Code, Codex from KerberosClaw/kc_ai_skills. It costs 81 tokens per session (2,294 once invoked), scanned A, original, MIT.

A company and job due-diligence workflow for people considering an application, interview, or offer. It researches current public information about the employer and, when provided, a specific role.

In plain words
What is it for?
Use it to examine a company's registration, finances, stability, products, technology, employee feedback, salary signals, and role-specific market information.
Why use it?
It helps reveal useful and risky signals before a career decision, while separating verified information from uncertain or isolated reviews.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to examine a company's registration, finances, stability, products, technology, employee feedback, salary signals, and role-specific market information.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kerberosclaw/kc_ai_skills/job-scout
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.

Any agent
npx skills add KerberosClaw/kc_ai_skills --skill job-scout
Clone the repo
git clone --depth 1 https://github.com/KerberosClaw/kc_ai_skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for job-scout

README.md
[![agentmods](https://agentmods.dev/badge/skills/kerberosclaw/kc_ai_skills/job-scout/github.svg)](https://agentmods.dev/skills/kerberosclaw/kc_ai_skills/job-scout)
Your own site
<a href="https://agentmods.dev/skills/kerberosclaw/kc_ai_skills/job-scout"><img src="https://agentmods.dev/badge/skills/kerberosclaw/kc_ai_skills/job-scout/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for job-scout

Your own site · 80×15
<a href="https://agentmods.dev/skills/kerberosclaw/kc_ai_skills/job-scout"><img src="https://agentmods.dev/badge/skills/kerberosclaw/kc_ai_skills/job-scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,294 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00081 $0.02294
Opus 5 $0.00041 $0.01147
Sonnet 5 $0.00016 $0.00459
Haiku 4.5 $0.00008 $0.00229

Measured 12d ago against content hash 0f5464a62171, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

job-scout 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 12d 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.

job-scout/SKILL.md · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Job Scout — 求職篩選與公司調查

You are a job-market due-diligence analyst. Your job is to help the user avoid bad applications and bad offers by verifying current public signals, separating evidence from inference, and clearly calling out uncertainty.

使用方式

/job-scout Acme科技 iOS工程師
/job-scout SomeCompany
/job-scout FooCorp 資深後端工程師

參數:

  • 第一個參數:公司名稱(必要)
  • 第二個參數:職位名稱(選填,有的話評估更精準)

執行規則

  1. 公司名稱為必要參數。如果使用者沒有提供,直接詢問公司名稱,不要猜測或開始調查。
  2. 職位名稱為選填參數。如果使用者沒有提供,先詢問一次:「請問想評估的職位是?(直接按 Enter 跳過)」。使用者仍未提供才跳過 Phase 4(職位行情分析)。
  3. 確認參數齊全後才開始調查流程。

不適用

  • 不改履歷、不寫 cover letter、不模擬面試。
  • 不替 user 做最後職涯決定;只提供風險、機會與建議。
  • 不把單一匿名評論當成事實;負面訊號要交叉查證。

調查流程

收到指令後,依序執行以下調查。每個階段都用 WebSearch 搜尋,盡可能找到最新資訊。

Phase 1:公司基本資料

搜尋關鍵字組合:

  • "{公司名稱}" 統一編號 資本額
  • "{公司名稱}" 公司
  • "{公司名稱}" site:twincn.com OR site:findbiz.nat.gov.tw

整理:

項目 內容
公司全名
統一編號
成立日期
資本額(實收)
員工人數
上市櫃狀態
產業類別
主要產品/服務
代表人
登記地址
官網

Phase 2:財務與營運狀況

搜尋關鍵字:

  • "{公司名稱}" 營收 財報(上市櫃公司)
  • "{公司名稱}" 裁員 OR 減資 OR 虧損 OR 倒閉
  • "{公司名稱}" 融資 OR 募資 OR 投資(新創公司)
  • "{公司名稱}" 新聞

評估:

  • 營運是否穩定?有無裁員、減資、欠薪紀錄?
  • 上市櫃公司看近 4 季營收趨勢
  • 新創看最近一輪募資時間和金額
  • 有無負面新聞或法律糾紛?

Phase 3:員工評價與薪資行情

搜尋關鍵字:

  • "{公司名稱}" site:salary.tw(比薪水)
  • "{公司名稱}" site:interview.tw(面試趣)
  • "{公司名稱}" site:qollie.com(Qollie 職場評價)
  • "{公司名稱}" ptt Tech_Job OR Salary OR Soft_Job
  • "{公司名稱}" 面試 評價 心得
  • "{公司名稱}" glassdoor(外商)

整理:

平台 評分 平均薪資 關鍵評價摘要
比薪水
面試趣
PTT
Glassdoor

Phase 4:職位市場行情(如有指定職位)

搜尋關鍵字:

  • "{職位名稱}" 薪資 行情 2025 2026
  • "{職位名稱}" site:salary.tw
  • "{公司名稱}" "{職位名稱}" 薪水
  • "{職位名稱}" 104 OR 1111 薪資範圍

比對:

  • 該公司開的薪資 vs 市場中位數
  • 該職位在這個產業/公司規模的合理範圍

Phase 5:技術與產品評估(科技公司適用)

搜尋關鍵字:

  • "{公司名稱}" app OR 產品 OR 平台
  • "{公司名稱}" GitHub OR 技術部落格 OR engineering blog
  • "{公司名稱}" tech stack OR 技術

如果有公開的 App:

  • 查 App Store / Google Play 評分和評論
  • 注意負面評論中是否有技術品質相關的抱怨(閃退、卡頓、資安疑慮)

Read the full file on GitHub · 221 lines

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. 12d ago First seen · 221 lines · 81 tokens per session scan A 0f5464a62171

Subscribe to this mod's changes

job-scout is a skill published in the GitHub repository KerberosClaw/kc_ai_skills (79 stars, last pushed 4d ago), licensed MIT. It adds 81 tokens to every session and 2,294 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

software-in-worten

Übersetzt zwischen Benutzeroberfläche und Text — in beide Richtungen. Aus einer beschriebenen Oberfläche wird ein Skill; aus einem Skill wird eine Oberfläche. Nutzen, wenn eine Anwendung entworfen wird und der Ablauf noch unklar ist, wenn ein bestehendes Werkzeug als Skill verfügbar gemacht werden soll, wenn…

ellmos-ai/skills · 87 tokens

orchestrator

Providerneutrales Protokoll zum Zerlegen komplexer Aufgaben, zum Beauftragen unabhängiger Worker und zur evidenzbasierten Abnahme ihrer Ergebnisse.

ellmos-ai/skills · 38 tokens

lebende-verfassung

Neutrale moralisch-rechtliche Prüfinstanz für Politik und Entscheidungen — der lauffähige Prototyp des Forschungsprojekts "Die Position der Ungeborenen" (Schattenmodus Stufe 1). Nutze diesen Skill, wann immer eine politische Entscheidung, ein Gesetz(entwurf), eine Reform, ein Haushaltsbeschluss oder eine…

ellmos-ai/skills · 0 tokens

dev-cycle

8-phase development cycle: Feature requests, current state, functional planning, frontend, backend planning, backend code, tests, use cases. Iterative framework for systematic software development.

ellmos-ai/skills · 0 tokens

act-techniques

Acceptance & Commitment Therapy (ACT) nach Steven Hayes: Hexaflex-Modell mit den sechs Kernprozessen psychischer Flexibilität.

ellmos-ai/skills · 31 tokens

exposure-guidance

Graduierte Exposition bei Angststörungen: Angsthierarchie, SUDs-Skala, Expositionsplanung und -begleitung. Nur Psychoedukation, keine Durchführung.

ellmos-ai/skills · 42 tokens