mirror of
https://github.com/fabro-sh/fabro.git
synced 2026-09-05 08:10:39 +00:00
664 lines
No EOL
20 KiB
JSON
664 lines
No EOL
20 KiB
JSON
{
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"title": "codex answer repro bool_true",
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"spec": {
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"run_id": "01KRCAQ9AS14KFCW4CXBZQ0CW9",
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"settings": {
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"project": {
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"name": null,
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"description": null,
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"metadata": {}
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},
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"workflow": {
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"name": null,
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"description": null,
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"graph": "workflow.fabro",
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"metadata": {}
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},
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"run": {
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"goal": {
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"type": "inline",
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"value": "codex answer repro bool_true"
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},
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"working_dir": null,
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"metadata": {
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"case": "bool_true",
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"qa": "codex-answer-repro"
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},
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"inputs": {},
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"model": {
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"provider": "anthropic",
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"name": "claude-sonnet-4-6",
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"fallbacks": []
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},
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"git": {
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"author": null
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},
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"prepare": {
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"commands": [],
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"timeout_ms": 300000
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},
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"execution": {
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"mode": "normal",
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"approval": "prompt"
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},
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"checkpoint": {
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"exclude_globs": []
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},
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"sandbox": {
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"provider": "daytona",
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"preserve": false,
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"stop_on_terminal": true,
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"devcontainer": false,
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"env": {},
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"docker": {
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"image": "buildpack-deps:noble",
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"network_mode": null,
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"memory_limit": 4000000000,
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"cpu_quota": 200000,
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"env_vars": {},
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"skip_clone": false
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},
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"daytona": {
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"auto_stop_interval": 30,
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"labels": {
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"repo": "fabro-sh/fabro"
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},
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"snapshot": {
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"name": "fabro-v8",
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"cpu": 8,
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"memory_gb": 16,
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"disk_gb": 20,
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"dockerfile": {
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"type": "inline",
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"value": "FROM ubuntu:24.04\n\nRUN apt-get update && apt-get install -y --no-install-recommends curl git ca-certificates build-essential pkg-config libssl-dev unzip python3 && rm -rf /var/lib/apt/lists/*\n\n# GitHub CLI\nRUN curl -fsSL https://cli.github.com/packages/githubcli-archive-keyring.gpg | dd of=/usr/share/keyrings/githubcli-archive-keyring.gpg && echo \"deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/githubcli-archive-keyring.gpg] https://cli.github.com/packages stable main\" | tee /etc/apt/sources.list.d/github-cli.list > /dev/null && apt-get update && apt-get install -y --no-install-recommends gh && rm -rf /var/lib/apt/lists/*\n\n# Rust\nRUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y\nENV PATH=\"/root/.cargo/bin:${PATH}\"\nRUN rustup toolchain install nightly-2026-04-14 --profile minimal --component clippy,rustfmt\nRUN cargo install cargo-nextest --locked\nENV CARGO_INCREMENTAL=0\n\n# Bun\nRUN curl -fsSL https://bun.sh/install | bash\nENV PATH=\"/root/.bun/bin:${PATH}\"\n\nWORKDIR /root\n"
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}
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},
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"network": null,
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"skip_clone": false
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}
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},
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"notifications": {},
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"interviews": {
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"provider": null,
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"slack": null
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},
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"agent": {
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"permissions": null,
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"mcps": {}
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},
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"hooks": [],
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"scm": {
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"provider": null,
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"owner": null,
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"repository": null,
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"github": null
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"pull_request": {
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},
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"artifacts": {
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"include": []
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},
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"integrations": {
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"github": {
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"permissions": {}
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}
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}
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}
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},
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"graph": {
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"name": "Interview",
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"nodes": {
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"start": {
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"id": "start",
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"attrs": {
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"label": {
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"String": "Start"
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},
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"shape": {
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"String": "Mdiamond"
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}
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}
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},
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"multi_select": {
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"id": "multi_select",
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"attrs": {
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"question_type": {
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"String": "multi_select"
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},
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"label": {
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"String": "Which supporting areas should the final summary emphasize?"
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},
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"shape": {
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"String": "hexagon"
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}
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}
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},
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"confirmation": {
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"id": "confirmation",
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"attrs": {
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"label": {
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"String": "Confirm that you want to continue into more structured questions."
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},
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"question_type": {
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"String": "confirmation"
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},
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"shape": {
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"String": "hexagon"
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}
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}
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},
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"exit": {
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"id": "exit",
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"attrs": {
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"label": {
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"String": "Exit"
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},
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"shape": {
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"String": "Msquare"
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}
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}
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},
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"multiple_choice": {
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"id": "multiple_choice",
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"attrs": {
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"question_type": {
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"String": "multiple_choice"
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},
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"label": {
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"String": "Which theme should be the center of the final summary?"
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},
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"shape": {
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"String": "hexagon"
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}
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}
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},
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"summarize": {
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"id": "summarize",
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"attrs": {
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"prompt": {
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"String": "Summarize the full human interview. Include each question and answer in order, then synthesize the user's priorities, constraints, and open questions. Use the human.gate.<node>.question and human.gate.<node>.answer context keys when present. Do not invent missing answers."
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},
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"shape": {
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"String": "tab"
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},
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"label": {
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"String": "Summarize Interview"
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},
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"fidelity": {
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"String": "summary:high"
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}
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}
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},
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"freeform": {
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"id": "freeform",
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"attrs": {
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"shape": {
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"String": "hexagon"
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},
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"question_type": {
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"String": "freeform"
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},
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"label": {
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"String": "Add any final context, constraints, or nuance for the summary."
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}
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}
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},
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"yes_no": {
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"id": "yes_no",
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"attrs": {
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"label": {
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"String": "Is this interview workflow easy to follow so far?"
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},
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"shape": {
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"String": "hexagon"
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},
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"question_type": {
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"String": "yes_no"
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}
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}
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}
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},
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"edges": [
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{
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"from": "start",
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"to": "yes_no",
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"attrs": {}
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},
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{
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"from": "yes_no",
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"to": "confirmation",
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"attrs": {
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"label": {
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"String": "[Y] Yes"
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}
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}
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},
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{
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"from": "yes_no",
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"to": "confirmation",
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"attrs": {
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"label": {
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"String": "[N] No"
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}
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}
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},
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{
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"from": "confirmation",
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"to": "multiple_choice",
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"attrs": {
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"label": {
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"String": "[Y] Continue"
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}
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}
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},
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{
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"from": "confirmation",
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"to": "multiple_choice",
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"attrs": {
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"label": {
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"String": "[N] Stop after this, but still summarize"
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}
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}
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},
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{
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"from": "multiple_choice",
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"to": "multi_select",
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"attrs": {
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"label": {
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"String": "[G] Goals"
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}
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}
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},
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{
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"from": "multiple_choice",
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"to": "multi_select",
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"attrs": {
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"label": {
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"String": "[R] Risks"
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}
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}
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},
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{
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"from": "multiple_choice",
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"to": "multi_select",
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"attrs": {
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"label": {
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"String": "[T] Tradeoffs"
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}
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}
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},
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{
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"from": "multiple_choice",
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"to": "multi_select",
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|
"attrs": {
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"label": {
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"String": "[Q] Open questions"
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}
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}
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},
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{
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"from": "multi_select",
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"to": "freeform",
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"attrs": {
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"label": {
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"String": "[S] Success criteria"
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}
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}
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},
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{
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"from": "multi_select",
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"to": "freeform",
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"attrs": {
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"label": {
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"String": "[B] Blockers"
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}
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}
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},
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{
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"from": "multi_select",
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"to": "freeform",
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"attrs": {
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"label": {
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"String": "[D] Decisions needed"
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}
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}
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},
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{
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"from": "multi_select",
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"to": "freeform",
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"attrs": {
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"label": {
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"String": "[N] Next steps"
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}
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}
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},
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{
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"from": "freeform",
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"to": "summarize",
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"attrs": {
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"freeform": {
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"Boolean": true
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}
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}
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},
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{
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"from": "summarize",
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"to": "exit",
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"attrs": {}
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}
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],
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"attrs": {
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"rankdir": {
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"String": "LR"
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},
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"goal": {
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"String": "codex answer repro bool_true"
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}
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}
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},
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"graph_source": "digraph Interview {\n graph [goal=\"Run a progressive human interview and summarize the answers\"]\n rankdir=LR\n\n start [shape=Mdiamond, label=\"Start\"]\n exit [shape=Msquare, label=\"Exit\"]\n\n yes_no [\n shape=hexagon,\n label=\"Is this interview workflow easy to follow so far?\",\n question_type=\"yes_no\"\n ]\n confirmation [\n shape=hexagon,\n label=\"Confirm that you want to continue into more structured questions.\",\n question_type=\"confirmation\"\n ]\n multiple_choice [\n shape=hexagon,\n label=\"Which theme should be the center of the final summary?\",\n question_type=\"multiple_choice\"\n ]\n multi_select [\n shape=hexagon,\n label=\"Which supporting areas should the final summary emphasize?\",\n question_type=\"multi_select\"\n ]\n freeform [\n shape=hexagon,\n label=\"Add any final context, constraints, or nuance for the summary.\",\n question_type=\"freeform\"\n ]\n summarize [\n shape=tab,\n label=\"Summarize Interview\",\n fidelity=\"summary:high\",\n prompt=\"Summarize the full human interview. Include each question and answer in order, then synthesize the user's priorities, constraints, and open questions. Use the human.gate.<node>.question and human.gate.<node>.answer context keys when present. Do not invent missing answers.\"\n ]\n\n start -> yes_no\n\n yes_no -> confirmation [label=\"[Y] Yes\"]\n yes_no -> confirmation [label=\"[N] No\"]\n\n confirmation -> multiple_choice [label=\"[Y] Continue\"]\n confirmation -> multiple_choice [label=\"[N] Stop after this, but still summarize\"]\n\n multiple_choice -> multi_select [label=\"[G] Goals\"]\n multiple_choice -> multi_select [label=\"[R] Risks\"]\n multiple_choice -> multi_select [label=\"[T] Tradeoffs\"]\n multiple_choice -> multi_select [label=\"[Q] Open questions\"]\n\n multi_select -> freeform [label=\"[S] Success criteria\"]\n multi_select -> freeform [label=\"[B] Blockers\"]\n multi_select -> freeform [label=\"[D] Decisions needed\"]\n multi_select -> freeform [label=\"[N] Next steps\"]\n\n freeform -> summarize [freeform=true]\n summarize -> exit\n}\n",
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"workflow_slug": "interview",
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"source_directory": "/Users/bhelmkamp/p/fabro-sh/fabro",
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"labels": {
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"case": "bool_true",
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"qa": "codex-answer-repro"
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},
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"server": {
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"version": "0.230.0-nightly.0"
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},
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},
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"subject": {
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"issuer": "https://github.com",
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"subject": "19"
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"manifest_blob": "1c2f42c56c499b6b77ec7a1be3b8da29772b13bbe4a3dd409878bde7478b46e8",
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"git": {
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"branch": "add-fabro-mcp-server",
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"sha": "55ff3d0601874e7319a150be8e6969baa3f6a4f5",
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"dirty": "dirty",
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"push_outcome": {
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"type": "succeeded",
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"remote": "origin",
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"branch": "add-fabro-mcp-server"
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}
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}
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},
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"web_url": "http://127.0.0.1:32276/runs/01KRCAQ9AS14KFCW4CXBZQ0CW9",
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"start": {
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"start_time": "2026-05-11T20:12:58.168105Z",
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"run_branch": "fabro/run/01KRCAQ9AS14KFCW4CXBZQ0CW9",
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"base_sha": "55ff3d0601874e7319a150be8e6969baa3f6a4f5"
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},
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"status": {
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"kind": "blocked",
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"blocked_reason": "human_input_required"
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},
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"status_updated_at": "2026-05-11T20:13:53.318756Z",
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"last_event_at": "2026-05-11T20:13:53.318756Z",
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"pending_control": null,
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"checkpoints": [
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{
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"seq": 19,
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"checkpoint": {
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"timestamp": "2026-05-11T20:13:01.104888Z",
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"current_node": "start",
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"completed_nodes": [
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"start"
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],
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"context_values": {
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"failure_signature": "",
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"internal.work_dir": "/home/daytona/workspace",
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"outcome": "succeeded",
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"internal.node_visit_count": 1,
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"graph.rankdir": "LR",
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"graph.goal": "codex answer repro bool_true",
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"current_node": "start",
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"failure_class": "",
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"internal.run_id": "01KRCAQ9AS14KFCW4CXBZQ0CW9",
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"internal.thread_id": null,
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"internal.retry_count.start": 0,
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"internal.fidelity": "compact"
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},
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"node_outcomes": {
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"start": {
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"status": "succeeded",
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"usage": null
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}
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},
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"next_node_id": "yes_no",
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"node_visits": {
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"start": 1
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}
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},
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"diff": {}
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},
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{
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"seq": 29,
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"checkpoint": {
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"timestamp": "2026-05-11T20:13:53.318481Z",
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"current_node": "yes_no",
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"start",
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"yes_no"
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],
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"node_retries": {},
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"internal.run_id": "01KRCAQ9AS14KFCW4CXBZQ0CW9",
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"internal.thread_id": "start",
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"internal.work_dir": "/home/daytona/workspace",
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"human.gate.label": "[Y] Yes",
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"failure_class": "",
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"current_node": "yes_no",
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"internal.fidelity": "compact",
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"graph.rankdir": "LR",
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"failure_signature": "",
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"human.gate.yes_no.question": "Is this interview workflow easy to follow so far?",
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"internal.retry_count.start": 0,
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"preferred_label": "[Y] Yes",
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"thread.start.current_node": "yes_no",
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"human.gate.selected": "Y",
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|
"human.gate.yes_no.label": "[Y] Yes",
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|
"internal.node_visit_count": 1,
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"outcome": "succeeded",
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"graph.goal": "codex answer repro bool_true"
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},
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"node_outcomes": {
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"start": {
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"status": "succeeded",
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"usage": null
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},
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"yes_no": {
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"status": "succeeded",
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"preferred_label": "[Y] Yes",
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"suggested_next_ids": [
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"confirmation"
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],
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"context_updates": {
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"human.gate.selected": "Y",
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"human.gate.yes_no.answer": "yes",
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"human.gate.label": "[Y] Yes",
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"human.gate.yes_no.label": "[Y] Yes",
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"human.gate.yes_no.question": "Is this interview workflow easy to follow so far?"
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},
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"usage": null
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}
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},
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"next_node_id": "confirmation",
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"git_commit_sha": "3ddbf2495e097ce0237f968431bf87f70df83555",
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"node_visits": {
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"yes_no": 1,
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