agent_action: Prompt-lab work item started
agent_action: Pinned repository checkout verified
agent_action: I’ll first map how this agent is structured and where external retrieval would plug...
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"
agent_action: `rg` is not installed in this environment, so I’m falling back to `find` and direct...
command: /bin/bash -lc "find . -path './node_modules' -prune -o -path './.git' -prune -o -type f | sed 's#"'^./##'"' | head -250"
command: /bin/bash -lc "find . -path './node_modules' -prune -o -path './.git' -prune -o -type f | sed 's#"'^./##'"' | head -250"
command: /bin/bash -lc 'ls -la'
command: /bin/bash -lc 'ls -la'
command: /bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"
command: /bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"
agent_action: The repository is a compact FastAPI plus Streamlit RAG app: server code, a vector s...
command: /bin/bash -lc "sed -n '1,260p' README.md"
command: /bin/bash -lc "sed -n '1,260p' README.md"
command: /bin/bash -lc "sed -n '1,260p' server/modules/llm.py"
command: /bin/bash -lc "sed -n '1,260p' server/modules/llm.py"
command: /bin/bash -lc "sed -n '1,320p' server/modules/vectorstore.py"
command: /bin/bash -lc "sed -n '1,320p' server/modules/vectorstore.py"
command: /bin/bash -lc "sed -n '1,320p' server/main.py"
command: /bin/bash -lc "sed -n '1,320p' server/main.py"
command: /bin/bash -lc "sed -n '1,240p' server/config.py"
command: /bin/bash -lc "sed -n '1,240p' server/config.py"
command: /bin/bash -lc "sed -n '1,240p' requirements.server.txt"
command: /bin/bash -lc "sed -n '1,240p' requirements.server.txt"
command: /bin/bash -lc "sed -n '1,260p' server/tests/test_hybrid_search.py"
command: /bin/bash -lc "sed -n '1,260p' server/tests/test_hybrid_search.py"
command: /bin/bash -lc "find . -path './.git' -prune -o -type f \\( -name '*.py' -o -name '*.md' -o -name '*.txt' -o -name '*.yaml' -o -name '*.yml' \\) -print | xargs grep -n \"agent\\|tool\\|retriev\\|source\\|search\\|Groq\\|LangChain\\|Tavily\\|Exa\\|Brave\\|Serp\\|Bing\\|Google\\|Perplexity\\|OpenAI\""
command: /bin/bash -lc "find . -path './.git' -prune -o -type f \\( -name '*.py' -o -name '*.md' -o -name '*.txt' -o -name '*.yaml' -o -name '*.yml' \\) -print | xargs grep -n \"agent\\|tool\\|retriev\\|source\\|search\\|Groq\\|LangChain\\|Tavily\\|Exa\\|Brave\\|Serp\\|Bing\\|Google\\|Perplexity\\|OpenAI\""
search: site:platform.openai.com/docs web search tool Responses API citations annotations O...
search: Tavily Search API official docs search extract crawl citations raw_content
search: official Google Gemini API grounding with Google Search citations grounding metadat...
search: site:docs.perplexity.ai Search API Perplexity official docs raw results citations
url: https://platform.openai.com/docs/guides/tools-web-search?api-mode=responses
search: 'url' in https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://cloud.google.com/vertex-ai/generative-ai/docs/grounding/grounding-with-your-data
agent_action: **Provider** I’d choose **Google Vertex AI/Gemini grounding with Google Search**, a...
result: Selected unknown