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 HHFinAi/claude-equity-research-skills --skill corporate-network-analysisgit clone --depth 1 https://github.com/HHFinAi/claude-equity-research-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/hhfinai/claude-equity-research-skills/corporate-network-analysis)<a href="https://agentmods.dev/skills/hhfinai/claude-equity-research-skills/corporate-network-analysis"><img src="https://agentmods.dev/badge/skills/hhfinai/claude-equity-research-skills/corporate-network-analysis/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/hhfinai/claude-equity-research-skills/corporate-network-analysis"><img src="https://agentmods.dev/badge/skills/hhfinai/claude-equity-research-skills/corporate-network-analysis.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 | $0.00075 | $0.01052 |
| Opus 5 | $0.00037 | $0.00526 |
| Sonnet 5 | $0.00015 | $0.00210 |
| Haiku 4.5 | $0.00007 | $0.00105 |
Grade A, and why
corporate-network-analysis 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Corporate Network Analysis
Exploit slow information diffusion through supply chain relationships and director interlocks to identify predictable stock returns. Academic research shows customer momentum yields ~150bps monthly alpha; board centrality generates ~4.68% annual risk-adjusted returns.
Core Investment Theses
- Supply Chain Momentum: When a customer gets a big order, upstream suppliers benefit with a lag (40% of shock diffuses over subsequent months)
- Director Interlock Signals: Shared board members facilitate information flow, M&A activity, and strategic alignment
- Cross-Holding Synergies: Executives/directors with positions in multiple companies may orchestrate beneficial strategic moves
Workflow
Phase 1: Identify Target Company Networks
1. Map supplier-customer relationships (>5% revenue materiality)
2. Identify board members and their other directorships
3. Track executive cross-company positions
4. Document insider holdings across connected firms
Phase 2: Data Collection
Use free data sources in this priority order:
| Relationship Type | Primary Source | How to Access |
|---|---|---|
| Suppliers/Customers | SEC 10-K Item 1/7 | EDGAR full-text search |
| Board Members | DEF 14A Proxy | EDGAR company filings |
| Insider Transactions | Form 3/4/5 | EDGAR insider filings |
| Beneficial Ownership | Schedule 13D/13G | EDGAR ownership filings |
| Institutional Holdings | Form 13F | EDGAR quarterly filings |
See references/sec-data-guide.md for detailed extraction procedures.
Phase 3: Network Construction
Build network graphs connecting companies through:
- Customer-supplier links (weighted by revenue %)
- Shared directors (first-degree: direct; second-degree: shared third board)
- Executive overlaps
- Cross-insider holdings
Calculate centrality metrics:
- Degree: Number of direct connections
- Betweenness: Importance in information flow paths
- Closeness: Speed of information propagation
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 · 122 lines · 75 tokens per session scan A afd13153d957
corporate-network-analysis is a skill published in the GitHub repository HHFinAi/claude-equity-research-skills (8 stars, last pushed 4mo ago), licensed MIT. It adds 75 tokens to every session and 1,052 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 2026-08-31.
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