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.
npx skills add yxndenyme/ai-career-roadmap-skill --skill generate-ai-career-roadmapgit clone --depth 1 https://github.com/yxndenyme/ai-career-roadmap-skillWrote 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/yxndenyme/ai-career-roadmap-skill/generate-ai-career-roadmap)<a href="https://agentmods.dev/skills/yxndenyme/ai-career-roadmap-skill/generate-ai-career-roadmap"><img src="https://agentmods.dev/badge/skills/yxndenyme/ai-career-roadmap-skill/generate-ai-career-roadmap/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/yxndenyme/ai-career-roadmap-skill/generate-ai-career-roadmap"><img src="https://agentmods.dev/badge/skills/yxndenyme/ai-career-roadmap-skill/generate-ai-career-roadmap.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 | $0.00100 | $0.02421 |
| Opus 5 | $0.00050 | $0.01210 |
| Sonnet 5 | $0.00020 | $0.00484 |
| Haiku 4.5 | $0.00010 | $0.00242 |
Grade A, and why
generate-ai-career-roadmap 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.
The source is not reproduced here
Licensed MIT-0
The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 325 B
- assets/profile-intake-template.md 1.1 KB
- assets/report-template.md 2.1 KB
- references/intake-profile.md 3.7 KB
- references/learning-plan-framework.md 5.1 KB
- references/report-contract.md 4.0 KB
- references/research-policy.md 4.7 KB
- references/role-taxonomy.md 4.4 KB
- scripts/validate_career_report.py 6.9 KB runs code
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 · 181 lines · 100 tokens per session scan A 163ba07d337b
generate-ai-career-roadmap is a skill published in the GitHub repository yxndenyme/ai-career-roadmap-skill (2 stars, last pushed 2mo ago), licensed MIT-0. It adds 100 tokens to every session and 2,421 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
learn
Knowledge compiler. Extracts patterns, decisions, and anti-patterns from completed campaigns and evolve cycles, then compiles them into structured wiki pages that integrate with existing knowledge rather than appending isolated files. Implements flush→compile→lint pipeline. Auto-triggered by /postmortem and /evolve…
zapier-demo
Walk a new user through setting up their first Zapier action and running it live — the smallest possible win. Asks what app they use, recommends one read action to enable, guides them to mcp.zapier.com to add it, then demonstrates it working in the same chat. Use when the user asks "show me how Zapier works", "set up…
ai-emotional-intelligence
Argues that emotional intelligence becomes strategically critical precisely because of AI -- not despite it -- and provides leaders with practices for developing the soft skills that constitute the human competitive advantage in an AI-saturated economy. Covers empathy, self-awareness, communication beyond technical…
prisoners-dilemma-and-cooperation
Analyzes the Prisoner's Dilemma and related non-cooperative game structures that cause rational actors to produce collectively suboptimal outcomes. Covers price war dynamics via the Cournot duopoly model, the Tragedy of the Commons for shared resources, and mechanisms for escaping destructive equilibria through…
ai-inclusive-collaboration
Provides a comprehensive framework for designing inclusive human-AI collaboration that keeps all stakeholders at the design table. Addresses exclusion dynamics, algorithm aversion, trust deficits, silo formation, and the human cost of automation-first strategies. Use when employees resist AI adoption, when AI design…
ai-learning-for-leaders
Guides non-technical leaders through building AI savviness without becoming AI experts, closing the gap between AI understanding and AI deployment. Applies the 'just savvy enough' principle and lifelong AI learning framework. Use when a leader feels inadequate about AI knowledge, defers too heavily to technologists…