Borrowing it
Nothing to install: this file belongs to karthikrshet/Career-Agents. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/karthikrshet/Career-Agents/main/.agents/skills/career-pipeline-upskill/SKILL.mdgit clone --depth 1 https://github.com/karthikrshet/Career-AgentsWrote 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/karthikrshet/career-agents/career-pipeline-upskill)<a href="https://agentmods.dev/skills/karthikrshet/career-agents/career-pipeline-upskill"><img src="https://agentmods.dev/badge/skills/karthikrshet/career-agents/career-pipeline-upskill/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/karthikrshet/career-agents/career-pipeline-upskill"><img src="https://agentmods.dev/badge/skills/karthikrshet/career-agents/career-pipeline-upskill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00014 | $0.00075 |
| Opus 5 | $0.00007 | $0.00037 |
| Sonnet 5 | $0.00003 | $0.00015 |
| Haiku 4.5 | $0.00001 | $0.00007 |
Grade A, and why
career-pipeline-upskill 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.
What it actually says
career-pipeline-upskill
Constructs a structured 30-day roadmap with daily milestones, hands-on projects, and authoritative reading to bridge identified skill gaps.
Usage
career-agents pipeline upskill <skillGap>
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.
- 12d ago First seen · 17 lines · 14 tokens per session scan A 867b1a6ee767
career-pipeline-upskill is a skill published in the GitHub repository karthikrshet/Career-Agents (44 stars, last pushed 6d ago), licensed MIT. It adds 14 tokens to every session and 75 once invoked, about $0.0001 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.
Other skills, from other repositories
baoyu-comic
A creator for educational comics, including biographies and tutorials, that turns supplied content or topics into illustrated comic pages.
concept-diagrams
Generate flat, minimal educational SVG visuals as HTML.
memento-flashcards
Spaced-repetition flashcards: create, review, quiz, export.
manim-video
Manim CE animations: 3Blue1Brown math/algo videos.
canvas
Fetch Canvas LMS courses and assignments via API token.
build-interactive-explainers
A guide for building interactive explainers, calculators, and simulations driven by an executable model. Users change inputs, steps, states, or events to understand a rule or see how a process develops over time.