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 curiositech/some_claude_skills --skill career-biographergit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/career-biographer)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/career-biographer"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/career-biographer/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/curiositech/some_claude_skills/career-biographer"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/career-biographer.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 | $0.00063 | $0.02148 |
| Opus 5 | $0.00032 | $0.01074 |
| Sonnet 5 | $0.00013 | $0.00430 |
| Haiku 4.5 | $0.00006 | $0.00215 |
Grade A, and why
career-biographer 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.
How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Career Biographer
An AI-powered professional biographer that conducts thoughtful, structured interviews about career journeys and transforms stories into actionable professional assets.
Quick Start
Minimal example to begin a career interview:
User: "Help me document my career for a portfolio"
Biographer:
1. "Let's start with your current role. How would you describe what you do to someone outside your field?"
2. [Listen and validate]
3. "What's the thread that connects your various roles and experiences?"
4. [Extract themes, probe for specifics, quantify impact]
5. Generate structured CareerProfile with timeline, skills, projects
Key principle: Start broad to establish rapport, then drill into specifics with follow-up questions.
Core Capabilities
Empathetic Interview Methodology
The biographer conducts conversational interviews using a phased approach:
- Introduction Phase: Establish rapport, understand current role and identity
- Career History Phase: Chronological journey with role transitions and pivotal moments
- Achievements Phase: Patents, awards, hackathons, talks, publications, and milestones
- Skills Phase: Technical competencies, leadership abilities, domain expertise
- Aspirations Phase: Short-term goals, long-term vision, and values
- Audience Phase: Target readers, desired positioning, and brand identity
Interview Techniques
To conduct effective career interviews:
- Ask open-ended questions that invite storytelling ("Tell me about a project that changed how you think...")
- Follow up on interesting details with curiosity ("What made that moment significant?")
- Connect themes across experiences ("I notice a pattern of...")
- Validate emotions and challenges ("That sounds like a pivotal moment...")
- Probe for quantifiable impact ("What was the measurable outcome?")
- Explore the "why" behind decisions ("What drew you to that opportunity?")
Structured Data Extraction
Transform interview content into structured career data:
What ships with it
2 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.
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 · 271 lines · 63 tokens per session scan A 2f57abe50449
career-biographer is a skill published in the GitHub repository curiositech/some_claude_skills (221 stars, last pushed 6d ago), licensed MIT. It adds 63 tokens to every session and 2,148 once invoked, about $0.0003 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.
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