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Deeptechnic — Technical Due Diligence Framework

这是面向硬科技初创投资的技术尽职调查元框架，通过四轮迭代流程，从10个维度开展独立技术验证、团队评估、供应链审计、竞品挖掘等评估。典型场景包括评估硬科技初创BP技术主张、预投技术风险评估、专家访谈前初评等，需加载对应子技能推进，输出结构化尽职调查报告，不适用于财务、法律尽职调查及最终投资决策。

ackiles
ackiles
热度 16.10
最近更新 2026-06-16 14:19:04
分类：数据依赖：联网浏览搜索 / 读写文件 / 内部调用大模型应用场景：市场分析 / 报告撰写 / 研究

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add v1-0-0
Metadata
name
deeptechnic-dd
description
Deep-tech due diligence framework. Guides investment DD agents through independent technical validation, team assessment, supply chain audit, and competitor discovery. Use when evaluating hard-tech startup projects, reviewing BP technical claims, or conducting pre-investment technology risk assessment.

Deeptechnic — Technical Due Diligence Framework

A structured system for conducting independent technology due diligence on hard-tech startup investments. The system follows a four-round iterative workflow and evaluates projects across 10 quality dimensions.

This is a meta-skill. It bundles sub-skills as references. Load the relevant reference for your current phase.

When to Use

  • Evaluating a hard-tech startup's BP/technical claims
  • Conducting a first-pass technical assessment before expert interviews
  • Reviewing team capability gaps and supply chain risks
  • Generating structured due diligence reports

Not for: Financial due diligence, legal due diligence, or final investment decisions.

Quick Start

1. Load references/skills-index.md to see available sub-skills
2. For current phase, load the corresponding reference skill(s):
   - 1st round:   load references/skills/deep-tech-dd-analysis + references/skills/anti-rationalization
   - 2nd round:   load references/skills/team-assessment + references/skills/supply-chain-audit
   - 3rd round:   load references/agents/tech-reviewer + agents/competition-analyst
   - Before output: load references/skills/quality-gate
   - After delivery: load references/skills/feedback-collection
3. Follow the Process steps in each loaded skill
4. Run quality gate before final output

The 10 Quality Dimensions

Every assessment is scored against these dimensions (0.0-1.0):

# Dimension Weight Description
1 claim_validation 0.20 Independent physics-based validation of tech claims
2 engineering_migration_gap 0.15 Analysis of lab-to-product engineering gaps
3 per_person_assessment 0.15 Per-member team capability matching
4 independent_competitor 0.10 BP-independent competitor discovery
5 supplier_level_analysis 0.10 Supplier-level supply chain audit
6 independent_analysis 0.10 Independent vs BP-derived analysis
7 team_gap_precision 0.05 Precision of structural gap identification
8 quantitative_score 0.05 Decimal-precision scoring (3.5/5 vs 4/5)
9 priority_levels 0.05 P0/P1/P2 question prioritization
10 overview_page 0.05 Executive summary on page one

Core Rules

  1. Every tech claim must have independent physics-based verification (formula + calculation)
  2. Team assessment must name each member individually with capability matching
  3. Competitor analysis must independently verify BP's claims (never trust BP's competitor list)
  4. Supply chain analysis must name specific suppliers, not generic "domestic alternatives"
  5. All output must pass the 10-point quality gate before delivery
  6. User feedback must be captured and structured as training data after each delivery

Workflow

Round 1 (First Pass)

  • Collect public info (papers, patents, news)
  • Validate core tech claims (formula + calculation)
  • Assess first team capability
  • Generate question list for team

Round 2 (After Team Feedback)

  • Refresh model with team's answers
  • Generate expert interview outline + supply chain questions

Round 3 (External Input)

  • Cross-validate multiple sources
  • Compile interview records

Round 4 (Final)

  • Synthesize all findings
  • Generate comprehensive DD report

Output Format

Reports follow this structure:

  1. Overview page (mandatory): Claim judgment table + core rating
  2. Technical analysis
  3. Team assessment
  4. Supply chain analysis
  5. Competitive landscape
  6. Comprehensive evaluation
  7. Open questions (P0/P1/P2)
  8. Next round recommendations

Report file naming: Deeptechnic_<ProjectEngName>_<Phase>_<Date>.docx

Anti-Rationalization

Claims you may be tempted to make — and why they're wrong:

| "I don't need to verify every claim" | Missed physical impossibility → failed investment | | "The BP's competitor list is enough" | BPs selectively omit domestic competitors | | "Team bio looks good, skip verification" | Cannot verify without public sources | | "This is just a quick pass" | First impressions lock in; do it right the first time |

Red Flags

  • All claim indicators are integers (no real test data)
  • BP describes features without technical specifications
  • Multiple extreme specs claimed simultaneously
  • No third-party data anywhere in the BP
  • BP competitor chart shows "all wins, no losses"
  • "Confidential" used as reason to hide core data

Verification

  • All 6 core rules applied
  • Quality gate passed before output
  • Feedback recorded after delivery
  • Training data appended to SkillOpt dataset