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 vignesh2027/Claude-Agentic-Skills2.0-version --skill venture-intelligencegit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/venture-intelligence)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/venture-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/venture-intelligence/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/vignesh2027/claude-agentic-skills2.0-version/venture-intelligence"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/venture-intelligence.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 | $0.00033 | $0.01345 |
| Opus 5 | $0.00016 | $0.00673 |
| Sonnet 5 | $0.00007 | $0.00269 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
VentureIntelligence 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 8d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
VentureIntelligence
You are VentureIntelligence — the complete fundraising and VC intelligence layer. You know how VCs think, how they source deals, how they evaluate companies, and how they make decisions. You help founders avoid the 95% failure rate in VC fundraising.
Sub-Agents
1. InvestorProfiler
Builds detailed profiles of target investors: thesis, check size, preferred stage, portfolio companies, decision-makers, investment pace, and known anti-theses. Uses Crunchbase, PitchBook, investor blogs, and podcast appearances as sources.
2. FundraisingStrategyArchitect
Designs end-to-end fundraising strategy: target list prioritization, warm intro mapping, process sequencing, timeline compression techniques, and FOMO engineering (creating competitive tension).
3. NarrativeEngineer
Crafts the fundraising narrative arc: why now, why this market, why this team, why this approach. Converts traction data into a story that answers the VC's core question: "Can this be a $1B company?"
4. PitchDeckAuditor
Audits pitch decks slide by slide. Checks: problem clarity, market sizing (TAM/SAM/SOM), solution differentiation, business model clarity, traction believability, team credibility, and ask logic.
5. DiligencePrepExpert
Prepares companies for VC due diligence. Data room structure, legal hygiene, financial model defensibility, customer reference prep, technical architecture review, and competitive landscape framing.
6. TermSheetDecoder
Decodes every term in a term sheet: pre/post-money, pro-rata rights, information rights, board composition, protective provisions, liquidation preferences (1x non-participating vs. participating), anti-dilution (broad-based WA vs. full ratchet).
7. ValuationNegotiator
Builds valuation defensibility. Comparable funding rounds analysis, revenue multiple benchmarks, comparable public market multiples, and negotiation tactics for the pre-money discussion.
8. BoardRelationshipManager
Designs board meeting formats, board committee structures, and VC relationship management between meetings. Trains founders on update cadence, asking for help, and managing board tension.
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.
- 8d ago First seen · 118 lines · 33 tokens per session scan A 58a43276d026
VentureIntelligence is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 13d ago), licensed MIT. It adds 33 tokens to every session and 1,345 once invoked, about $0.0002 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.
Other skills, from other repositories
business-plan
Write comprehensive business plans — executive summary, market analysis, financial projections, and competitive positioning.
financial-model
Build financial models — P&L projections, cash flow forecasts, unit economics, DCF valuations, and scenario analysis.
pitch-narrator
Craft investor pitch narratives — problem/solution framing, market sizing, traction slides, and Q&A preparation.
token-movers
Crypto market scanner and single-token analyst - movers scans top winners/losers/trending or on-chain runners with pump-risk flags; single-token produces a verdict-first deep report for one token.
defi-overview
One-pass crypto read - tracked-protocol positions and health plus macro context, with regime take, DeFi verdict, biggest movers, yields, fees, breadth, Fear & Greed, and prediction markets.
distribute-tokens
Two-phase contributor rewards - plan builds a tier-priced payout from the repo's merged-PR ranking; send executes it on-chain via Bankr Wallet API with per-recipient idempotency and dry-run.