career-ops
- Repo stars 48,511
- License MIT
- Author updated Live
- Author repo career-ops
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 94 / 100 · audit passed
- Author / version / license
- @santifer · MIT
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: career-ops
description: AI job search command center -- evaluate offers, generate CVs, scan portals, track applications…
category: ai
runtime: no special runtime
---
# career-ops output preview
## PART A: Task fit
- Use case: AI job search command center -- evaluate offers, generate CVs, scan portals, track applications Determine the mode from $mode: | Input | Mode | |-------|------| | (empty / no args) | discovery -- Show command menu | | JD text or URL (no sub-command) | auto-pipeline | runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Mode Routing / Discovery Mode (no arguments) / Context Loading by Mode” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “AI job search command center -- evaluate offers, generate CVs, scan portals, track applications Determine the mode from $mode: | Input | Mode | |-------|------| | (empty / no args) | discovery -- Show command menu | | JD text or URL (no sub-command) | auto-pipeline | runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Mode Routing / Discovery Mode (no arguments) / Context Loading by Mode” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/career-ops`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Mode Routing / Discovery Mode (no arguments) / Context Loading by Mode”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: career-ops
description: AI job search command center -- evaluate offers, generate CVs, scan portals, track applications…
category: ai
source: santifer/career-ops
---
# career-ops
## When to use
- AI job search command center -- evaluate offers, generate CVs, scan portals, track applications Determine the mode fro…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Mode Routing / Discovery Mode (no arguments) / Context Loading by Mode” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "career-ops" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Mode Routing / Discovery Mode (no arguments) / Context Loading by Mode
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} career-ops -- Router
Mode Routing
Determine the mode from $mode:
| Input | Mode |
|---|---|
| (empty / no args) | discovery -- Show command menu |
| JD text or URL (no sub-command) | auto-pipeline |
oferta |
oferta |
ofertas |
ofertas |
contacto |
contacto |
deep |
deep |
interview-prep |
interview-prep |
pdf |
pdf |
training |
training |
project |
project |
tracker |
tracker |
pipeline |
pipeline |
apply |
apply |
scan |
scan |
batch |
batch |
patterns |
patterns |
followup |
followup |
update |
update |
Auto-pipeline detection: If $mode is not a known sub-command AND contains JD text (keywords: "responsibilities", "requirements", "qualifications", "about the role", "we're looking for", company name + role) or a URL to a JD, execute auto-pipeline.
If $mode is not a sub-command AND doesn't look like a JD, show discovery.
Discovery Mode (no arguments)
Show this menu:
career-ops -- Command Center
Available commands:
/career-ops {JD} → AUTO-PIPELINE: evaluate + report + PDF + tracker (paste text or URL)
/career-ops pipeline → Process pending URLs from inbox (data/pipeline.md)
/career-ops oferta → Evaluation only A-F (no auto PDF)
/career-ops ofertas → Compare and rank multiple offers
/career-ops contacto → LinkedIn power move: find contacts + draft message
/career-ops deep → Deep research prompt about company
/career-ops interview-prep → Generate company-specific interview prep doc
/career-ops pdf → PDF only, ATS-optimized CV
/career-ops training → Evaluate course/cert against North Star
/career-ops project → Evaluate portfolio project idea
/career-ops tracker → Application status overview
/career-ops apply → Live application assistant (reads form + generates answers)
/career-ops scan → Scan portals and discover new offers
/career-ops batch → Batch processing with parallel workers
/career-ops patterns → Analyze rejection patterns and improve targeting
/career-ops followup → Follow-up cadence tracker: flag overdue, generate drafts
/career-ops update → Update career-ops system files with diff preview + compat check
Inbox: add URLs to data/pipeline.md → /career-ops pipeline
Or paste a JD directly to run the full pipeline.
Context Loading by Mode
After determining the mode, load the necessary files before executing:
Modes that require _shared.md + their mode file:
Read modes/_shared.md + modes/{mode}.md
Applies to: auto-pipeline, oferta, ofertas, pdf, contacto, apply, pipeline, scan, batch
Standalone modes (only their mode file):
Read modes/{mode}.md
Applies to: tracker, deep, interview-prep, training, project, patterns, followup
Modes delegated to subagent:
For scan, apply (with Playwright), and pipeline (3+ URLs): launch as Agent with the content of _shared.md + modes/{mode}.md injected into the subagent prompt.
Agent(
subagent_type="general-purpose",
prompt="[content of modes/_shared.md]\n\n[content of modes/{mode}.md]\n\n[invocation-specific data]",
description="career-ops {mode}"
)
Execute the instructions from the loaded mode file.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review