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 w95/awesome-claude-corporate-skills --skill deal-sourcinggit clone --depth 1 https://github.com/w95/awesome-claude-corporate-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/w95/awesome-claude-corporate-skills/deal-sourcing)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/deal-sourcing"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/deal-sourcing/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/w95/awesome-claude-corporate-skills/deal-sourcing"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/deal-sourcing.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 | $0.00000 | $0.00808 |
| Opus 5 | $0.00000 | $0.00404 |
| Sonnet 5 | $0.00000 | $0.00162 |
| Haiku 4.5 | $0.00000 | $0.00081 |
Grade A, and why
deal-sourcing 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.
This is a copy
95% identical to deal-sourcing — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deal Sourcing
description: PE deal sourcing workflow — discover target companies, check CRM for existing relationships, and draft personalized founder outreach emails. Use when sourcing new deals, prospecting companies in a sector, or reaching out to founders. Triggers on "find companies", "source deals", "draft founder email", "check if we've seen this company", or "outreach to founder".
Workflow
This skill follows a 3-step sourcing pipeline:
Step 1: Discover Companies
Research and identify potential target companies based on the user's criteria:
- Sector/industry focus: Ask the user what space they're looking in (e.g., "B2B SaaS in healthcare", "industrial services in the Southeast")
- Deal parameters: Revenue range, EBITDA range, growth profile, geography, ownership type (founder-owned, PE-backed, corporate carve-out)
- Sources: Use web search to find companies matching criteria. Look at industry reports, conference attendee lists, trade publications, and competitor landscapes
- Output: A shortlist of companies with: name, description, estimated revenue/size, location, founder/CEO name, website, and why they fit the thesis
Step 2: CRM Check
Before outreach, check if the company or founder already exists in the firm's CRM:
- Search the user's email (Gmail) for prior correspondence with the company or founder
- Search Slack for any internal mentions or prior discussions about the target
- Ask the user: "Have you or your team had any prior contact with [Company]?"
- Flag any existing relationships, prior passes, or known context
- Output: For each company, note: "New" (no prior contact), "Existing" (prior correspondence found — summarize), or "Previously Passed" (if evidence of a prior pass)
Step 3: Draft Founder Outreach
Draft personalized cold emails to founders/CEOs:
- Tone: Professional but warm. Not overly formal — founders respond better to genuine, concise outreach
- Structure:
- Brief intro — who you are and your firm (ask user for their firm intro if not known)
- Why this company caught your attention — reference something specific (product, market position, growth)
- What you're looking for — partnership, not just a transaction
- Soft ask — "Would you be open to a brief conversation?"
- Personalization: Reference the company's specific product, recent news, or market position. Never use generic templates
- Length: 4-6 sentences max. Founders are busy
- Voice matching: If the user has sent prior outreach emails, study them to match their tone and style. Search Gmail for "sent" emails with keywords like "reaching out", "introduction", "partnership" to find examples
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 · 66 lines · 0 tokens per session scan A acfccee526e5
deal-sourcing is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (198 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 808 tokens. A static security scan graded it A with 0 findings. It is 95% identical to deal-sourcing, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
financial-expert
A financial research skill for China and Hong Kong securities, funds, company finances, economic indicators, research reports, announcements, news, and business-risk data. It returns data and neutral analysis rather than placing trades or recommending investments.
stock-analysis-lead
Orchestrate a US-stock investment analysis — classify sector archetype, fetch SEC filings, dispatch a tiered fan-out of six vertical equity-research agents (business model, earnings quality, balance sheet, management, industry, peer comparison) over a validated JSON findings contract, then synthesize a buy/hold/sell…
stock-business-review
Review a US-listed company's business model and revenue structure for an equity-research workup. Covers product/service mix, customer concentration, geographic exposure, industry position, revenue-growth decomposition (organic vs acquired vs price vs volume), and information-tier discipline (which numbers are facts vs…
stock-earnings-quality-review
Review a US-listed company's earnings quality, cash-flow integrity, and operating leverage for an equity-research workup. Covers operating cash flow vs net income drift, free cash flow trajectory, capex character (maintenance vs expansion), equity issuance / shareholder-return yield, revenue-quality signals…
stock-balance-sheet-review
Review a US-listed company's balance sheet health for an equity-research workup. Covers net-debt/EBITDA leverage, current ratio, cash runway, goodwill concentration and impairment history, DSO trend, inventory days, off-balance-sheet items (operating leases, contingent liabilities), and pension underfunding. Trigger…
stock-industry-review
Review a US-listed company's industry position and competitive moat for an equity-research workup. Covers Porter Five Forces scan, market-share trend (absolute and relative to industry growth), TAM size and trajectory, unit economics where disclosed (LTV/CAC, unit gross margin), moat classification (network / brand /…