Claude Code Guide is a reference collection for configuring and using Claude Code, Anthropic’s command-line coding agent. Developers use it to learn commands, skills, agents, MCP, automation, security, integrations, and troubleshooting. Its catalogue add-ons provide many of the documented skills and agents.
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 zebbern/claude-code-guide --skill vc-industry-researchgit clone --depth 1 https://github.com/zebbern/claude-code-guideWrote 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/zebbern/claude-code-guide/vc-industry-research)<a href="https://agentmods.dev/skills/zebbern/claude-code-guide/vc-industry-research"><img src="https://agentmods.dev/badge/skills/zebbern/claude-code-guide/vc-industry-research/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/zebbern/claude-code-guide/vc-industry-research"><img src="https://agentmods.dev/badge/skills/zebbern/claude-code-guide/vc-industry-research.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 | $0.00083 | $0.01526 |
| Opus 5.5 | $0.00033 | $0.00610 |
| Sonnet 5.5 | $0.00017 | $0.00305 |
| Haiku 4.5 | $0.00008 | $0.00153 |
Grade A, and why
vc-industry-research 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 1mo 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Primary Market Industry Research Report
Generate professional industry research reports in an institutional primary-market (PE/VC) research style.
Reference Source
- Type: Uploaded artifact (PDF)
- Reference File Type: PDF
- Languages: Chinese or English (auto-detect from user query; default to user's language)
Supported Outputs
- PDF (default)
- DOCX
- PPTX (if explicitly requested)
Default output: PDF. If user explicitly requests DOCX or PPTX, honor that request.
Workflow
- Understand the research scope from user query: target industry, sub-topics, depth, page count
- Determine report style based on user preference or task context:
- Style A (Deep Discussion): Opinion-heavy, TMT/tech focus, numbered chapters (01, 02...), no TOC
- Style B (Traditional Sector): Data-heavy, many charts and tables, TOC with multi-level numbering
- Plan content structure using the appropriate structure contract (see references)
- Research and gather data using web search and data source tools as needed
- Review investment & financing history for the sector: search for key funding rounds, deal sizes, lead investors, IPO/exit events, and capital flow trends in the target industry. Sources include Crunchbase, PitchBook, CB Insights, IT桔子, 烯牛数据, and public deal announcements
- Generate the report following the style and structure contracts precisely
- Review for completeness: ensure all exhibits are numbered, sources cited, and formatting consistent
Style Selection Guide
Choose the report style based on context:
| Indicator | Use Style A (Deep Discussion) | Use Style B (Traditional) |
|---|---|---|
| Sector | TMT, AI, Software, SaaS | Consumer, Healthcare, Industrials, Materials |
| Tone | Opinion-forward, thesis-driven | Data-driven, objective |
| Charts | Moderate (native charts, benchmark tables for AI research) | Dense (pie charts, bar charts, line charts) |
| TOC | No | Yes, with 3-level hierarchy + dot-leaders + page numbers |
| Chapter numbers | 01, 02, 03... in red/dark-red | 1, 1.1, 1.2, 2.1... in black |
| Page count | 15-25 pages typical | 30-60 pages typical |
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.
- 1mo ago First seen · 141 lines · 83 tokens per session scan A a12c14006201
vc-industry-research is a skill published in the GitHub repository zebbern/claude-code-guide (4,678 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 1,526 once invoked, about $0.0003 per session on Opus 5.5. 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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