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-new-application)<a href="https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-new-application"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-new-application/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.
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/career-engine-new-application"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/career-engine-new-application.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00143 | $0.18437 |
| Opus 5 | $0.00072 | $0.09218 |
| Sonnet 5 | $0.00029 | $0.03687 |
| Haiku 4.5 | $0.00014 | $0.01844 |
Grade D, and why
career-engine-new-application scanned grade D with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
If you are in Claude Code, you can also find it at `~/.claude/skills/career-data/` if a Code-side copy exists. **Important:** if the user runs both Chat and Code (or Cowork), they must apply this update twice — once in C Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **Path A:** `rm -rf "$PIPE"` How it starts
The opening of the file, as written. The whole thing — 641 lines — stays where its author put it; the contents beside it link to each section on GitHub.
New Application — Per-Role Pipeline
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 covers Step 0.10 and Steps 1 through 7 of the New Applications pipeline. Step 0.10 runs once before the per-role loop begins. Steps 1 through 7 repeat for each role in the processing queue. The structured JD was fetched in Step 0.5 and is in memory — pass it directly without re-fetching.
The pipeline produces two deliverables per role: a CV DOCX and a cover letter DOCX. The CV goes through: draft, gatekeeper, recruiter review, revision, gatekeeper (post-revision). The cover letter is written after the final CV, from exactly three content inputs — the final CV, Role emphasis, and Why I Want This Role (see Step 5's input contract). The recruiter review, including its interview-trigger gaps, is user-facing feedback surfaced in Step 7d's feedback file — it is never passed to the letter-writer.
career-datadata root (R-37). The personal-data files —01-writing-rules.md,02-professional-background.md,03-framework.md,linkedin-profile.md,pipeline-preferences.json,delivered-letters/, and the user's.dotx— load from${CAREER_DATA}/references/, the path the orchestrator resolves in itscareer-datadiscovery preflight. Every other file (self-checks,REFERENCES.md, skill docs, default.dotxtemplates) stays on${CLAUDE_PLUGIN_ROOT}. If${CAREER_DATA}is not set (direct or standalone invocation outside the orchestrator), locate thecareer-dataskill yourself, confirmcareer-data-marker.json, and apply the orchestrator's healthy / damaged / absent outcomes before reading. A configured user's missingcareer-datais a hard stop — never silently fall back to blank templates.
Universal spawn parameter —
gap_handling_mode(2026-07-14).$GAP_HANDLING_MODEis resolved once per run (orchestrator config resolution:pipeline-preferences.json→gap_handling;disabledwhen the value isdisabledor empty,enabledotherwise — an absent key on an older config meansenabled). Every subagent spawn in this pipeline passesgap_handling_mode=$GAP_HANDLING_MODE, exactly likeCAREER_DATA— every agent, every round, every re-spawn and crash-recovery fallback, no exceptions. Whendisabled, no agent may produce, request, or enforce gap framing anywhere: the coach's outline and review carry no gap directives, the recruiter asks no writer to address a gap in a document, the gatekeeper's Gate 0 gap-handling keyword exception never applies, and no document acknowledges a gap (the letter-side never-name-the-gap rule applies regardless of mode). This is a one-word routing token — for the letter-writer it rides inside its input contract's routing-token allowance, never as content.
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.
- 10d ago First seen · 641 lines · 143 tokens per session scan D 389ed331d318
career-engine-new-application is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 28d ago), licensed MIT. It adds 143 tokens to every session and 18,437 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it D with 2 findings (enumerates other installed skills, recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…