#!/usr/bin/env bash # 引文回查脚本(C1 / benchmark_v2 附录 B R-G1~R-G4 的留痕工具) # 用法: verify_quotes.sh → 对每条拟用引文做 grep -F 命中计数,输出 FILEHITSQUOTE # 口径: HTML/MD 直读逐字(口径1)。空白不敏感命中(口径2)与 PDF 解码转写(口径3)见 verify_quotes.py RAW=/app/system/agents/deep-research/train/hunt/sources_raw r() { local f="$1"; local s="$2"; local n n=$(grep -o -F -- "$s" "$RAW/$f" 2>/dev/null | wc -l) printf '%s\t%s\t%s\n' "$f" "$n" "$s"; } echo "### S1 anthropic-multiagent.html" r anthropic-multiagent.html '15× more tokens than chats' r anthropic-multiagent.html '90.2% on our internal research eval' r anthropic-multiagent.html 'Simple fact-finding requires just 1 agent with 3-10 tool calls' r anthropic-multiagent.html 'more than 10 subagents with clearly divided responsibilities' r anthropic-multiagent.html 'start with short, broad queries' r anthropic-multiagent.html "Each subagent needs an objective, an output format" r anthropic-multiagent.html 'agents continuing when they already had sufficient results' r anthropic-multiagent.html 'scouring the web endlessly for nonexistent sources' r anthropic-multiagent.html 'Adding source quality heuristics' r anthropic-multiagent.html "game of telephone" r anthropic-multiagent.html 'saving its plan to Memory' r anthropic-multiagent.html '3-5 subagents in parallel rather than serially' r anthropic-multiagent.html 'use 3+ tools in parallel' r anthropic-multiagent.html 'spawning 50 subagents for simple queries' r anthropic-multiagent.html 'CitationAgent processes the documents' r anthropic-multiagent.html 'do the cited sources match the claims' r anthropic-multiagent.html 'did it use primary sources over lower-quality secondary sources' r anthropic-multiagent.html 'Research demands the flexibility to pivot' r anthropic-multiagent.html 'chose SEO-optimized content farms over authoritative' r anthropic-multiagent.html 'examine all available tools first' r anthropic-multiagent.html 'duplicated work investigating current 2025 supply chains' r anthropic-multiagent.html 'match tool usage to user intent' r anthropic-multiagent.html 'Research Lead' r anthropic-multiagent.html 'citation accuracy' echo "### S7/S8/S9/S10/S11/S17" r gpt-researcher-readme.md "utilize 'planner' and 'execution'" r gpt-researcher-readme.md 'publisher' r gpt-researcher-readme.md 'the more sites we scrape the less chances of incorrect data' r storm-readme.md 'generating long articles with citations into two steps' r storm-readme.md 'Perspective-Guided Question Asking' r storm-readme.md 'pre-writing' r storm-readme.md 'Stanford OVAL' r storm-paper-arxiv.html 'source bias transfer' r storm-paper-arxiv.html 'over-association of unrelated facts' r storm__full-paper.html 'source bias transfer' r storm__full-paper.html 'over-association of unrelated facts' r storm__full-paper.html 'citation recall' r storm__full-paper.html 'citation precision' r storm__full-paper.html 'we calculate the' r storm__full-paper.html 'based on the definition in Gao et al' r storm__full-paper.html '84.83' r storm__full-paper.html '85.18' r storm__full-paper.html 'Severely lacking' r storm__full-paper.html 'Exemplary in breadth' r mbfc-methodology.html 'a minimum of 10 headlines and 5 full news stories' r mbfc-methodology.html 'no universally accepted scientific formula exists' r mbfc-methodology.html 'remains primarily tailored to the political landscape of the United States' r mbfc-methodology.html 'structured human assessments' echo "### S14/S15/S16/S18/S19" r openai__deep-research-mcp-server-README.md 'relies specifically on Search and Fetch tools' r openai__deep-research-mcp-server-README.md "do not call fetch again for that same file" r openai__deep-research-mcp-server-README.md 'Include inline citations and return all source metadata' r openai__deep-research-mcp-server-README.md 'Prioritize reliable, up-to-date sources' r google__gemini-deep-research.md 'creates a multi-step research plan for you to either revise or approve' r google__gemini-deep-research.md 'comprehensive report with key findings and links to original sources' r google__gemini-deep-research.md 'hundreds' r google__gemini-deep-research.md 'browses' r hapgood__SIFT-four-moves.md 'Stop, Investigate the source, find better coverage' r hapgood__SIFT-four-moves.md 'Trace claims, quotes, and media back to the original context' r hapgood__SIFT-four-moves.md 'stopping periodically and reevaluating our reaction or search strategy is key' r hapgood__SIFT-four-moves.md 'Just as when you hear a rumor you want to know who the source is before reacting' r open_deep_research__README.md '$45.98' r open_deep_research__README.md '$187.09' r open_deep_research__README.md 'RACE' r open_deep_research__README.md 'Summarization' r open_deep_research__README.md 'Compression' r open_deep_research__README.md 'Final Report'