Dossier
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile.
Before & after
Same prompt, same agent — the only difference is the skill.
I can help you research a venture capital firm. I'd look at their portfolio companies, partners, investment thesis, and recent activity. You could find information from their website, press releases, and news articles. I'd put together a summary of what they invest in, how much they typically raise, and any relevant news about them. That would help you understand what they're looking for. Do you want me to include anything specific like their LinkedIn profiles or recent funding announcements? This would give you some background, though the research will be general.
DOSSIER: TechVenture Capital Research Date: 2026-07-31 | Confidence: HIGH HYPOTHESIS (yours to test): "TechVenture invests in infrastructure plays, not applications; they will pass on a B2B SaaS Series A." VERDICT: MOSTLY TRUE (8/10 confidence) Portfolio is 73% infrastructure (data, APIs, dev tools) vs 27% applications. But they made 2 app investments in 2025 when founders had engineering backgrounds. Your pitch risks misalignment. ORGANIZATION FACTS Founded: 2016 | AUM: 340M | Typical Check: 2-5M | SaaS: 31% of portfolio | Sectors: DevTools 42%, Data 31%, AI 18%, Fintech 9% 12-MONTH ACTIVITY TIMELINE Jan 2026: Led Series B for DataFlow (API platform, 15M) Mar 2026: Joined Series A for NeuroSync (AI research, 8M) May 2026: Launched Climate Tech Fund (50M) Jul 2026: Passed on 3 B2B SaaS pitches (public feedback: "too many competitors") KEY PARTNERS & BETS • Sarah Chen (general partner, focus: developer tools) — 8 board seats, all infrastructure • Marcus Kumar (analyst, focus: AI + data) — covers recent SaaS exceptions • Fund II (closed 2024): Weighted 60% infrastructure, only 3 app companies NETWORK & REPUTATION ✓ Strong exits: 5 portfolio companies acquired by Google, Meta, Stripe ✓ Network depth: CEO relationships with 40+ enterprise IT leaders ✗ Red flag: Passed on 2 AI SaaS pitches (2025, 2026) citing "market saturation" ✗ Weak consumer tech track record: 1 consumer investment (2017), returned 0.3x REALTED FLAGS 1. Diversity: 3 of 6 partners are ex-Stripe (may favor payments/fintech) 2. Founder type: All funded founders have PhD or C-suite background (you: bootcamp grad → risk) 3. Lead times: Typical decision window 8-12 weeks (long for A round) 4. Valuation bias: Median Series A marked at 20M (vs. market 15M) CONVERSATION HOOKS • Ask Sarah about her developer tool thesis (she leads this) • Lead with: "We're infrastructure for engineering teams, not just another SaaS app" • Mention: Their DevTools pattern matching your category • Avoid: Comparing to their SaaS losers (NeuroSync positioning) PREP CHECKLIST ☐ Research their 3 most recent Series A exits (check Crunchbase for outcomes) ☐ Prep answer: "Why infrastructure, not SaaS?" with 2-minute elevator pitch ☐ Know Sarah's 8 board seats (her companies, her preferences) ☐ Prepare for 10-week decision window (not a quick yes) SOURCES AUDITED: ✓ Crunchbase (6 deals verified) ✓ LinkedIn (partner profiles, connections) ✓ SEC EDGAR (any LP relationships, filings) ✓ News: PitchBook + TechCrunch (2025-2026) ✗ Insider interviews unavailable (timing)
About this skill
name: dossier description: Use when Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile.
Dossier
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person/company]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the dossier skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Dossier; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: dossier
description: Use this skill when asked for background research, diligence, or meeting prep on a specific company, person, nonprofit, or government organization.
version: 1.0.0
category: Research & Data / Research
author: AgentVolt
license: proprietary
tags:
- research-data
- research
---
# Dossier
Produces a decision-grade, hypothesis-tested dossier on a specific entity rather than a generic profile — forcing the user to state upfront what they believe and want verified or disproven.
## When to use
… (sign up to view the full skill)More research & data skills
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