Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add spinningrachel/career-engine/plugin install career-engineWrote 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.
[](https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-setup)<a href="https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-setup"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-setup.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00106 | $0.19455 |
| Opus 5 | $0.00053 | $0.09728 |
| Sonnet 5 | $0.00021 | $0.03891 |
| Haiku 4.5 | $0.00011 | $0.01946 |
Grade B, and why
career-engine-setup scanned grade B with 1 finding 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 8d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- Do NOT write this preference to `~/.claude/settings.json` — that location is reachable only from the user's own machine and silently falls back to the default everywhere else. The pipeline still reads it as a legacy fa How it starts
The opening of the file, as written. The whole thing — 1,013 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Career Engine Onboarding
Registry: this pipeline is listed in the Pipeline Registry in
skills/career-engine/SKILL.md. Actions owned by another pipeline's registry row are out of scope here — route to that pipeline instead of improvising.
This skill sets up the plugin for a new user. It builds the three reference files that all pipeline agents read before writing anything:
01-writing-rules.md— fabrication guards, attribution rules, framing constraints, contact details02-professional-background.md— role facts, approved content, portfolio03-framework.md— positioning, voice, methodology, domain narratives
Output target — the career-data skill, not in-plugin references (R-37). Setup builds these files into the user's external career-data skill, not into the plugin's references/. Author the data files (01/02/03, linkedin-profile.md, pipeline-preferences.json, delivered-letters/, and the user's .dotx) into a working career-data/ skill directory as you go. Installing that directory as a real skill is environment-specific and is the single step that most often goes wrong — follow references/career-data-skill-handoff.md (a.k.a. "Appendix A"): in Cowork, you cannot save a skill directly, so you emit a /skill-creator handoff prompt the user pastes into Chat (skills are shared between Chat and Cowork, so it lands in both); in Claude Code, you write ~/.claude/skills/career-data/ directly. The dedicated Build & install step at the end of this skill runs that handoff. Write the first backup export of career-data to the output folder. The plugin's in-plugin references/ stay as blank {{...}} templates — never personalized.
Placeholder resolution (single-build). Identity and config values are NOT substituted into the plugin's agent/skill/reference files — that would personalize the shared build. They live in career-data and agents resolve them at runtime: identity from career-data 01-writing-rules.md §8, output folder and CV template from the career-data config (see CLAUDE.md → Placeholder resolution). Every step below writes these values into career-data, never into plugin files.
How onboarding works: You send your existing career materials. The agent reads them and synthesizes 03-framework.md. You review it and respond — with feedback or approval. That response triggers a targeted interview that fills gaps and captures what the materials didn't fully show. Integration (Notion, output path) comes after.
Run order matters. Phase 0 (environment check) → Phase 1 (identity) → Phase 2 (content submission) → Phase 3 (synthesis) → Phase 4 (review and interview) → Phase 5 (integration) → Phase 6 (permissions) → Phase 7 (job-preferences) → Build & install career-data (the closing handoff step). Phases 5–7 can be deferred — the pipeline can run with Phases 1–4 complete. Whenever a setup session ends (all phases done, or the user stops), run the Build & install step so the work authored this session actually becomes an installed skill.
Onboarding can be paused and resumed. The Phase 4 interview in particular can take time. If the user needs to stop, they can resume later by running /career-engine:setup --phase 4. The state of 03-framework.md is preserved between sessions — sections already confirmed have no [DRAFT] or [REVIEW] markers; sections still needing work do. The pre-flight check uses this to report progress accurately.
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.
- 8d ago First seen · 1,013 lines · 106 tokens per session scan B 903f84f41cc7
career-engine-setup is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 26d ago), licensed MIT. It adds 106 tokens to every session and 19,455 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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