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 hr-network-analystgit 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/hr-network-analyst)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/hr-network-analyst"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/hr-network-analyst/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/hr-network-analyst"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/hr-network-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 103 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 140 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00089 | $0.01444 |
| Opus 5 | $0.00044 | $0.00722 |
| Sonnet 5 | $0.00018 | $0.00289 |
| Haiku 4.5 | $0.00009 | $0.00144 |
Grade A, and why
hr-network-analyst 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 7d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HR Network Analyst
Applies graph theory and network science to professional relationship mapping. Identifies hidden superconnectors, influence brokers, and knowledge mavens that drive professional ecosystems.
Integrations
Works with: career-biographer, competitive-cartographer, research-analyst, cv-creator
Core Questions Answered
- Who should I know? (optimal networking targets)
- Who knows everyone? (superconnectors for referrals)
- Who bridges worlds? (cross-domain brokers)
- How does influence flow? (information/opportunity pathways)
- Where are structural holes? (untapped connection opportunities)
Quick Start
User: "Who are the key connectors in AI safety research?"
Process:
1. Define boundary: AI safety researchers, 2020-2024
2. Identify sources: arXiv, NeurIPS workshops, Twitter clusters
3. Compute centrality: betweenness (bridges), eigenvector (influence)
4. Classify by archetype: Connector, Maven, Broker
5. Output: Ranked list with network position rationale
Key principle: Most valuable people aren't always most famous—they connect otherwise disconnected worlds.
Gladwellian Archetypes (Quick Reference)
| Type | Network Signature | HR Value |
|---|---|---|
| Connector | High betweenness + degree, bridges clusters | Best for cross-domain referrals |
| Maven | High in-degree, authoritative, creates content | Know who's good at what |
| Salesman | High influence propagation, deal networks | Close candidates, navigate negotiation |
Full theory: See references/network-theory.md
Centrality Metrics (Quick Reference)
| Metric | Meaning | When to Use |
|---|---|---|
| Betweenness | Controls information flow | Finding gatekeepers, brokers |
| Degree | Raw connection count | Maximizing referral reach |
| Eigenvector | Quality over quantity | Access to power, rising stars |
| PageRank | Endorsed by important others | Thought leaders |
| Closeness | Can reach anyone quickly | Information spreading |
What ships with it
7 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.
- 7d ago First seen · 163 lines · 89 tokens per session scan A cc11c467761c
hr-network-analyst is a skill published in the GitHub repository curiositech/some_claude_skills (218 stars, last pushed 4d ago), licensed MIT. It adds 89 tokens to every session and 1,444 once invoked, about $0.0004 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 2026-09-03.
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