"""Summarize observed research coverage; does not claim an exhaustive AI census.""" import argparse from collections import Counter import json from pathlib import Path import sys from urllib.parse import urlsplit ROOT = Path(__file__).resolve().parents[1] DATA = json.loads((ROOT / 'content/research/ai-companies.seed.json').read_text()) AUDIT = json.loads((ROOT / 'content/research/ai-companies.coverage.json').read_text()) SOURCES = json.loads((ROOT / 'content/research/ai-companies.sources.json').read_text()) TARGET = ROOT / '.artifacts/reports/02-coverage-and-gaps.md' SOURCE_SLUG = 'ai-company-research/02-coverage-and-gaps' BASE = '/docs/other-research/ai-company-research/overview' def source_register(): sources = SOURCES['sources'] ids = {s['id'] for s in sources} assert len(ids) == len(sources) and ids == {f'S{i:02}' for i in range(1, 17)} assert SOURCES['scopeConfirmedAt'] <= DATA['asOf'] host_map = {} for source in sources: assert source['status'] in {'candidate-audit', 'targeted', 'pending', 'context', 'access-limited', 'per-company'} assert source['boundary'] and source['nextCheck'] if source['url']: assert urlsplit(source['url']).scheme in {'http', 'https'} and urlsplit(source['url']).netloc for host in source['hosts']: assert host not in host_map, f'Duplicate source host: {host}' host_map[host] = source['id'] assigned = {key: [] for key in ids} for evidence in DATA['evidence']: owner = host_map.get(urlsplit(evidence['url']).netloc) if owner is None: owner = 'S12' if any(word in evidence['kind'] for word in ('官方', '公司自述', '公司披露')) else 'S16' assigned[owner].append(evidence) assert sum(len(v) for v in assigned.values()) == len(DATA['evidence']) statuses = {'candidate-audit': '候选池逐条已读', 'targeted': '定向使用，未穷尽', 'pending': '候选台账待建', 'context': '背景研究', 'access-limited': '访问受限', 'per-company': '随公司逐条核对'} lines = ['', '## 来源清单与验收边界', '', SOURCES['provenance'], '', '每条证据在下表只计入一个渠道：先按所列域名归属，再将类型明确标为官方/公司自述/公司披露的剩余项计入S12，其余计入S16。公司可跨渠道出现，所以公司数不可跨行相加。零条证据表示尚未进入研究表，不表示该来源没有相关公司。背景报告不承担公司发现全集的角色。', '', '| 来源 | 当前状态 | 证据 / 公司 / 观测数 | 已核对范围 | 剩余核查 |', '| --- | --- | --- | --- | --- |'] for source in sources: evidence = assigned[source['id']] evidence_ids = {e['id'] for e in evidence} company_ids = {e['companyId'] for e in evidence if e['companyId']} observations = sum(o['evidence'] in evidence_ids for o in DATA['observations']) name = f"[{source['name']}]({source['url']})" if source['url'] else source['name'] lines.append(f"| {source['id']} {name} | {statuses[source['status']]} | {len(evidence)} / {len(company_ids)} / {observations} | {source['boundary']} | {source['nextCheck']} |") lines += ['', 'Dealroom、Product Hunt、机器之心与36氪入口于2026-10-30重新访问。官网首页可读不证明已取得完整筛选结果；安全检测页面不作为文章内容。候选池之外的来源边界尚需建立可回查条目，完成前不宣布来源清单已全部覆盖。', ''] return lines def context_methods(): evidence = {e['id']: e for e in DATA['evidence']} rows = [s for s in SOURCES['sources'] if s.get('methodology')] assert {s['id'] for s in rows} == {'S06', 'S07', 'S08', 'S09'} lines = ['', '## 背景基准适用性与缺项', '', '以下核对背景资料的方法及适用范围，不是公司名录的完整覆盖。原始方法记录与全局核查随研究版本进入同一数据库；没有把行业汇总值新增为任何公司的收入观测。', '', '| 来源与证据 | 样本与统计单位 | 时间 | 本次读取范围 | 可用于什么 | 主要限制 |', '| --- | --- | --- | --- | --- | --- |'] for source in rows: m = source['methodology'] assert m['checkedAt'] <= DATA['asOf'] assert all(m.get(key) for key in ('sample', 'unit', 'period', 'access', 'use', 'limit', 'evidenceIds')) assert all(eid in evidence and evidence[eid]['companyId'] is None for eid in m['evidenceIds']) assert not any(o['evidence'] in m['evidenceIds'] for o in DATA['observations']) proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in m['evidenceIds']) lines.append(f"| {source['id']} {source['name']}：{proof} | {m['sample']}；{m['unit']} | {m['period']} | {m['access']} | {m['use']} | {m['limit']} |") lines += ['', '本表的应用解释属于研究判断。选样、分母、时间或指标不同会造成表观差异；这些差异不单独证明财务造假，也不能作为给未知公司填补收入的依据。', ''] return lines def candidate_register(): batches = DATA.get('candidateBatches', []) companies = {c['id']: c for c in DATA['companies']} categories = {c['id']: c['name'] for c in DATA['categories']} known_sources = {s['id'] for s in SOURCES['sources']} evidence = {e['id']: e for e in DATA['evidence']} assert len({b['id'] for b in batches}) == len(batches) all_ids = [r['id'] for b in batches for r in b['records']] assert len(set(all_ids)) == len(all_ids) lines = [] statuses = {'pending-year': '成立年待核', 'pending-ai': 'AI主营待核', 'linked': '已关联公司', 'existing-outside-cohort': '已有关联，年份范围外', 'outside-cohort': '范围外或既有业务，不新增公司', 'promotion': '推广活动，非公司新增'} for batch in batches: assert batch['sourceId'] in known_sources assert batch['accessedAt'] <= DATA['asOf'] assert any(e['url'] == batch['url'] for e in DATA['evidence']) rows = batch['records'] counts = Counter(r['status'] for r in rows) assert sum(counts.values()) == len(rows) lines += ['', f"## {batch['sourceId']} 候选核对（{batch['id']}）", '', f"[发现页面]({batch['url']})，读取于{batch['accessedAt']}。{batch['scope']}", '', f"本批{len(rows)}条：{counts['linked']}条关联公司、{counts['existing-outside-cohort']}条关联范围外对照、{counts['outside-cohort']}条范围外不新增公司、{counts['pending-year']}条成立年待核、{counts['pending-ai']}条AI主营待核、{counts['promotion']}条推广活动。完整来源覆盖标记：{'已完成' if batch['complete'] else '未完成'}。主营或产品任务的初分类不计入主公司表数量，只有已关联的公司记录进入对应公司明细。候选与缺项随研究版本保存在文档站同一SQLite的研究元数据中。", '', '| 发现条目 | 主营或产品任务初分 | 核对状态 | 关联公司 | 核对证据 | 限制 |', '| --- | --- | --- | --- | --- | --- |'] for row in rows: assert row['categoryId'] in categories assert row['status'] in statuses assert all(eid in evidence for eid in row.get('evidenceIds', [])) if row['status'] in {'outside-cohort', 'pending-ai'}: assert row.get('evidenceIds') and not row.get('companyId') name = f"[{row['name']}]({row['url']})" if row['url'] else row['name'] company = '—' if row.get('companyId'): assert row['companyId'] in companies c = companies[row['companyId']] company = f"[{c['name']}]({BASE}?company={c['id']}#research-company-detail)" proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in row.get('evidenceIds', [])) or '成立证据待补，产品页读取状态见候选记录' category = f"[{categories[row['categoryId']]}]({BASE}?category={row['categoryId']})" lines.append(f"| {name} | {category} | {statuses[row['status']]} | {company} | {proof} | {row['note']} |") if batch['sourceId'] == 'S04': lines += ['', '产品页可读只表示有可访问的资料；本批未将所有产品页完成公司、技术或财务深查。既有直接HTTP采集返回403，当前采用可读的公开页面响应，不声称取得底层全量列表；后续公开档案与未读页面继续保留缺项。', ''] else: lines += ['', '发现条目和可读正文分开记录；登录外壳、读取失败或搜索摘录不充当已阅读全文。关联公司以列出的原始材料补证，仍保留技术、主体与收入未核事项。', ''] return lines def uncertain_ai_followups(): original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'ai-unclear'} rows = [row for batch in DATA.get('candidateBatches', []) if batch['id'].startswith('YC-AI-UNCLEAR-') for row in batch['records']] if not rows: return [] urls = [row['url'] for row in rows] assert len(set(urls)) == len(urls), 'Duplicate AI-relevance follow-up URL' rechecks = {row['ycId']: row for row in DATA.get('directoryRechecks', [])} counts = Counter(row['status'] for row in rows) assert set(counts) <= {'linked', 'pending-ai'} for row in rows: assert row['url'] in original and row.get('evidenceIds') baseline = original[row['url']] if row['status'] == 'linked': assert rechecks[baseline['ycId']]['companyId'] == row['companyId'] else: assert not row.get('companyId') and baseline['ycId'] not in rechecks unread = len(original) - len(rows) assert unread >= 0 return ['', '## 原AI主营不明名单的后续覆盖', '', f"原名单{len(original)}项，已有后续记录{len(rows)}项：{counts['linked']}项关联公司、{counts['pending-ai']}项仍待核AI主营，{unread}项尚无本批系列的后续记录。计数按原始YC页面去重；EveryApp此前的独立复核与末批记录不重复相加。", '', '读完名单只证明每项有可回查的处理记录，不证明待核项均为AI公司，也不证明法律主体、收入或技术效果已独立验证。原始发现审计保持不变，成立年范围外/缺失、成立冲突及其他来源的缺项仍单列。', ''] def founding_year_followups(): original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'date-conflict'} rows = [row for batch in DATA.get('candidateBatches', []) if batch['id'].startswith('YC-DATE-CONFLICT-') for row in batch['records']] urls = [row['url'] for row in rows] assert len(set(urls)) == len(urls), 'Duplicate founding-conflict follow-up URL' assert set(urls) <= set(original), 'Unknown founding-conflict follow-up URL' evidence = {row['id']: row for row in DATA['evidence']} for row in rows: assert row['status'] == 'pending-year' and not row.get('companyId') assert row.get('evidenceIds') and all(eid in evidence for eid in row['evidenceIds']) assert all(evidence[eid]['companyId'] is None for eid in row['evidenceIds']) unread = len(original) - len(rows) return ['', '## 原成立年冲突名单的后续覆盖', '', f"原名单{len(original)}项，已有后续记录{len(rows)}项，均保留成立年待核，{unread}项尚无本系列后续记录。当前业务初分类见候选表，不计入主公司表及收入统计。", '', '2025旧品牌发布可证明当时已有产品材料；当前目录的2026字段、批次、条款日期和运营者名称不能单独证明法律主体成立或新旧主体连续。未据此强改成立年。Layers当前AI核心仍另待核。', ''] def directory_rechecks(): rows = DATA.get('directoryRechecks', []) if not rows: return [] original = {row['ycId']: row for row in AUDIT['records']} companies = {c['id']: c for c in DATA['companies']} evidence = {e['id']: e for e in DATA['evidence']} assert len({row['ycId'] for row in rows}) == len(rows) lines = ['', '## 原候选池的后续复核', '', '原始1,428条读取快照与初筛计数保持不变；下表记录当时未入表、后续补足证据后进入公司表的项目。初筛未通过不是永久排除。后续入表不回写为当时已匹配，也不重复计入928条原始新增目录项。', '', '| 原候选 | 原始状态 | 后续公司记录 | 复核证据 | 处理与限制 |', '| --- | --- | --- | --- | --- |'] for row in rows: baseline = original[row['ycId']] assert baseline['status'] == row['originalStatus'] assert row['reviewedAt'] <= DATA['asOf'] and row['reason'] assert row['originalStatus'] in {'ai-unclear', 'year-outside-or-missing', 'date-conflict'} company = companies[row['companyId']] assert row['evidenceIds'] and all(eid in evidence for eid in row['evidenceIds']) proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in row['evidenceIds']) lines.append(f"| [{baseline['name']} · YC{row['ycId']}]({baseline['source']}) | {row['originalStatus']} | [{company['name']}]({BASE}?company={company['id']}#research-company-detail) | {proof} | {row['reviewedAt']}：{row['reason']} |") lines += ['', f"已记录{len(rows)}条后续复核入表；其余未入表候选仍按原状态保留缺项，不能把这一批复核视为完成全部模糊项。", ''] return lines def render(): cov = DATA['coverage'] companies = DATA['companies'] depth = sum(bool(c.get('profileOnly')) for c in companies) origin = sum(bool(c.get('profileOnly')) or c.get('directoryOrigin') == 'yc-2025-2026' for c in companies) promoted = origin - depth reviewed = sum(bool(c.get('profileOnly')) and '人工复核' in c.get('classificationBasis', '') for c in companies) years = Counter(c['year'] for c in companies) income = Counter(c['revenueStatus'] for c in companies) technical = Counter(c.get('technicalReview', {}).get('level', 'unreviewed') for c in companies) assert cov['profilesRead'] + cov['failedProfiles'] == cov['candidateRecords'] assert cov['matchingProfiles'] == cov['existingProfiles'] + cov['newProfiles'] assert cov['matchingProfiles'] + cov['otherOrMissingYear'] + cov['unclearAI'] + cov['dateConflicts'] == cov['profilesRead'] assert origin == cov['newProfiles'] assert AUDIT['accessedAt'] == cov['accessedAt'] assert AUDIT['counts'] == cov assert len(AUDIT['records']) == cov['profilesRead'] assert Counter(x['status'] for x in AUDIT['records']) == { 'imported': cov['newProfiles'], 'existing': cov['existingProfiles'], 'year-outside-or-missing': cov['otherOrMissingYear'], 'ai-unclear': cov['unclearAI'], 'date-conflict': cov['dateConflicts']} assert len({x['ycId'] for x in AUDIT['records']}) == len(AUDIT['records']) excluded_years = Counter(x['foundedYear'] for x in AUDIT['records'] if x['status'] == 'year-outside-or-missing') outside_years = {year: count for year, count in excluded_years.items() if year is not None} assert all(year not in (2025, 2026) for year in outside_years) assert sum(outside_years.values()) + excluded_years[None] == cov['otherOrMissingYear'] year_detail = '、'.join(f'{year}年{count}项' for year, count in sorted(outside_years.items())) lines = ['# AI 公司资料覆盖与缺项', '', f"截至 {DATA['asOf']}，研究表含{len(companies):,}条公司或产品记录。YC候选池有逐条读取审计；其他来源为定向补充。清单尚不能作为全球AI公司普查，也不能将收入未知解释为零。", '', '验收范围已于2026-10-30确认为：以确认的公开来源清单为边界，逐条核对并标明缺项。下方区分已逐条审计的候选池与定向补充来源；已使用某来源不代表该来源已被完整覆盖。', '', f"[分类和数据工作台]({BASE})链接原始证据，[收入样本快照](/docs/other-research/ai-company-research/income-snapshot)展示当前可计算的MRR样本。", '', '## 候选池与公司表的关系', '', '| 环节 | 记录数 | 含义 |', '| --- | --- | --- |', f"| YC批次候选 | {cov['candidateRecords']:,} | 从公开镜像发现，随后读取YC官方页面 |", f"| 官方页面读取 | {cov['profilesRead']:,} | 此候选池读取失败{cov['failedProfiles']}条 |", f"| 初筛匹配 | {cov['matchingProfiles']:,} | 成立年及AI相关描述通过初筛，尚非逐家商业验证 |", f"| 与原表重合 | {cov['existingProfiles']} | URL匹配，未再次新增 |", f"| 新增目录记录 | {cov['newProfiles']:,} | 原始入表来源，后续深化不改变发现计数 |", f"| 原目录列为范围外年份 | {sum(outside_years.values())} | {year_detail}；原快照自述，不是独立登记核验 |", f"| 原目录未给成立年 | {excluded_years[None]} | 与已列范围外年份分开，仍待补证 |", f"| AI业务待确认 | {cov['unclearAI']} | 不强行把背景关键词当主营 |", f"| 成立年与批次冲突 | {cov['dateConflicts']} | 另保留核查记录 |", '', f"全表由{depth}条目录基础项和{len(companies)-depth}条个案或平台记录组成。候选池已匹配项之外另有{len(companies)-cov['matchingProfiles']}条记录，包含其他来源及发布/转型对照；其中已有{promoted}条原目录记录深化为个案，仍保留目录来源。两种统计边界不同。候选池数字只是该镜像快照的覆盖，Bud等后续定向补充不回填为原候选池已覆盖。", '', '## 成立年与证据深度', '', '| 维度 | 当前记录 | 解读 |', '| --- | --- | --- |', f"| 记录为2025年成立 | {years[2025]} | 成立来源和精度见公司明细 |", f"| 记录为2026年成立 | {years[2026]} | 不将产品发布日期代替成立日 |", f"| 成立年未知或范围外 | {sum(v for k,v in years.items() if k not in (2025,2026))} | 发布/转型对照单列，不进入两年成立分组 |", f"| 目录业务分类人工复核 | {reviewed} | 仅复核主营分类，不代表技术或财务审计 |", f"| 其他目录基础项 | {depth-reviewed} | 规则初分或资料不足，继续待复核 |", f"| 有团队数字 | {sum(c['team'] is not None for c in companies)} | 多为自报Team Size或Employees，时点与口径不统一 |", f"| 专项技术证据记录 | {len(companies)-technical['unreviewed']} | 其中{technical['description']}条自述、{technical['public-artifact']}条公开材料、{technical['independent-test']}条第三方评测 |", f"| 企业披露收入线索 | {income['self']} | 含公司或交易当事方披露、历史、下界及币种不明，不等于可比ARR |", f"| 仅平台收入线索 | {income['platform']} | 同时有企业披露者计入上一行，不重复计数 |", f"| 仅第三方估算 | {income['estimate']} | 不与直接披露混合 |", f"| 暂无可用收入数字 | {income['unknown']} | 包含尚未逐家搜索的目录项，不代表没有收入 |", '', '## 业务分类与数据入口', '', '| 业务类别 | 记录数 |', '| --- | --- |', ] counts = Counter(c['cat'] for c in companies) for category in DATA['categories']: lines.append(f"| [{category['name']}]({BASE}?category={category['id']}) | {counts[category['id']]} |") lines += ['', '## 已使用来源的分布', '', f"{len(DATA['evidence']):,}条证据记录对应{len({e['url'] for e in DATA['evidence']}):,}个不同URL。不同URL不自动构成独立验证；同一声明可能由公司、投资方和媒体重复转述。", '', '| 来源 | 证据记录 | 不同URL | 用途及限制 |', '| --- | --- | --- | --- |', ] families = [('YC官方目录', 'www.ycombinator.com', '公司自述的成立、团队与业务；英文及加速器样本偏多'), ('TrustMRR', 'trustmrr.com', '支付平台重建指标及方法；公开者存在选择偏差，非财务审计'), ('a16z Speedrun', 'speedrun.a16z.com', '投资机构中的公司介绍及收入声明；存在利益关系'), ('TechCrunch', 'techcrunch.com', '原始采访或报道；转述公司数字不等于查账'), ('Sacra', 'sacra.com', '第三方估算；与直接披露分开')] included = set() for name, host, note in families: entries = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc == host] included.add(host) lines.append(f"| {name} | {len(entries)} | {len({e['url'] for e in entries})} | {note} |") others = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc not in included] lines.append(f"| 其他官网、评测及公开资料 | {len(others)} | {len({e['url'] for e in others})} | 按每条来源限制理解，不能统一当作独立证据 |") lines += uncertain_ai_followups() lines += founding_year_followups() lines += directory_rechecks() lines += source_register() lines += context_methods() lines += candidate_register() lines += ['', '## 尚未满足的研究条件', '', '行业ARR比较仍缺统一业务截止日、币种、经常性定义和业务边界。现有平台MRR可描述已采集产品，不足以代表全部新公司。技术评测只覆盖所列版本与任务，不宜跨领域汇总为统一强弱分数。', '', '下一轮优先补收入线索的日期及合同定义、成立年冲突、AI主营仍待核项、非YC和非英文来源，以及停止服务或被收购案例。这样能减少“只见赢家”和“只见融资公司”的偏差。公开来源池之外的未披露公司仍无法证明已被穷尽。', '', ] return '\n'.join(lines) def main(): parser = argparse.ArgumentParser(description=__doc__) parser.add_argument('--check', action='store_true') parser.add_argument('--document-export', type=Path) args = parser.parse_args() content = render() if args.check: if args.document_export is not None: bundle = json.loads(args.document_export.read_text()) stored = next((d['content'] for d in bundle['documents'] if d['sourceSlug'] == SOURCE_SLUG), None) if stored != content: sys.exit('Research coverage report differs; review and regenerate') print('Research coverage accounting verified; supplied document export compared when requested') else: TARGET.parent.mkdir(parents=True, exist_ok=True) TARGET.write_text(content) print(TARGET.relative_to(ROOT)) if __name__ == '__main__': main()