agent-cooking-cli 0.2.0

Evidence-first, artifact-driven bug triage workflow for CLI agents

agent-cooking-cli

Evidence-first workflows for agents. Generate a workspace, then execute steps with auditable artifacts.

中文版 README

What It Does

agent-cooking-cli gives your agent a "recipe" (profile) and a persistent workspace so it can work without relying on chat memory.

The workspace lives under TRIAGEFLOW_ROOT/triage/ and includes:

• triage/case.yaml: input and context (facts, not guesses)
• triage/evidence/ + triage/evidence/index.md: evidence snippets with EIDs (E001, E002, ...)
• triage/facts.md: facts only (each cites EIDs)
• triage/hypotheses.md: hypotheses (must cite EIDs)
• triage/directions.md: top directions (must cite EIDs)

Hard rule: no evidence -> no hypothesis/direction.

Install

pipx (recommended)

pipx install git+https://github.com/bigmoon-dev/agent-cooking-cli.git
kitchen --help

Editable install (dev)

python -m pip install -e .
python -m triageflow --help

The console entry point is kitchen, but python -m triageflow ... is the most reliable way to run.

5-Minute MVP

This is the fastest verified path to experience the full workflow from install to a validated result.

What you will do:

1. Create a triage workspace
2. Attach a small UART log
3. Capture one evidence item (E001)
4. Add one fact backed by evidence
5. Add one hypothesis backed by evidence
6. Build one direction
7. Validate the workspace

When it succeeds, you will have a complete triage/ folder with evidence and decision artifacts on disk.

Run It

python3 -m pip install -e .
export TRIAGEFLOW_ROOT=/tmp/triageflow-mvp
rm -rf "$TRIAGEFLOW_ROOT"
mkdir -p "$TRIAGEFLOW_ROOT"

cat > "$TRIAGEFLOW_ROOT/uart.log" <<'EOF'
boot
panic: watchdog
stack: ...
reboot
EOF

python3 -m triageflow start --profile embedded_system_v1

printf "mvp reboot\naffects all\nfw-mvp\nhw-mvp\nopen lid, pair, wait\nnow\n" | \
  python3 -m triageflow round run 0 --no-editor

printf "mixed\nn\nunknown\nunknown\nunknown\nunknown\npanic\n" | \
  python3 -m triageflow round run 1 --no-editor

python3 -m triageflow evidence attach --uart-log "$TRIAGEFLOW_ROOT/uart.log"
python3 -m triageflow evidence hunt

python3 -m triageflow facts add \
  --text "panic observed during flow" \
  --evidence E001

python3 -m triageflow hypotheses add \
  --hypothesis "watchdog reset triggers reboot" \
  --evidence E001 \
  --test "print reset cause / wdt reason"

python3 -m triageflow direction-build --overwrite --top-n 1
python3 -m triageflow validate
python3 -m triageflow status
python3 -m triageflow next

Expected Result

You should see output like:

• Initialized .../triage
• Next: round run 0
• Added E001: .../triage/evidence/log/E001_log.txt
• Added F... to .../triage/facts.md
• Added H... to .../triage/hypotheses.md
• Wrote .../triage/directions.md (1 directions)
• OK: validation passed
• Next: validate

Files You Should See

After the MVP completes, these files should exist:

• $TRIAGEFLOW_ROOT/triage/profile.yaml
• $TRIAGEFLOW_ROOT/triage/case.yaml
• $TRIAGEFLOW_ROOT/triage/evidence/index.md
• $TRIAGEFLOW_ROOT/triage/evidence/log/E001_log.txt
• $TRIAGEFLOW_ROOT/triage/facts.md
• $TRIAGEFLOW_ROOT/triage/hypotheses.md
• $TRIAGEFLOW_ROOT/triage/directions.md

What You Just Proved

This MVP shows that triageflow can:

• persist a workspace on disk
• capture evidence with stable EIDs
• enforce evidence-backed facts and hypotheses
• generate directions from evidence-backed hypotheses
• validate the resulting workspace

If you want a more guided version of this flow, see docs/quickstart.md.

Concepts

The triage workspace lives under TRIAGEFLOW_ROOT/triage/ and is designed to be stable and reviewable.

Key idea: evidence first. Facts, hypotheses, and directions should cite evidence IDs.

Quickstart (Embedded)

Pick a workspace root (outside your code repo) and run:

export TRIAGEFLOW_ROOT=/path/to/workspace
python -m triageflow start --profile embedded_system_v1

# Keep running this; it tells you the next command.
python -m triageflow next

If you want a minimal reproducible demo, create a small UART log:

cat > "$TRIAGEFLOW_ROOT/uart.log" <<'EOF'
boot
panic: watchdog
stack: ...
reboot
EOF

Then follow next.

Legacy MVP Script (Deprecated)

This older script remains for reference. Prefer the 5-Minute MVP section above, or docs/quickstart.md.

export TRIAGEFLOW_ROOT=/path/to/workspace
rm -rf "$TRIAGEFLOW_ROOT/triage"
mkdir -p "$TRIAGEFLOW_ROOT"

cat > "$TRIAGEFLOW_ROOT/uart.log" <<'EOF'
boot
panic: watchdog
stack: ...
reboot
EOF

python -m triageflow init --profile embedded_system_v1

printf "mvp reboot\naffects all\nfw-mvp\nhw-mvp\nopen lid, pair, wait\nnow\n" | \
  python -m triageflow round run 0 --no-editor

printf "mixed\nn\nunknown\nunknown\nunknown\nunknown\npanic\n" | \
  python -m triageflow round run 1 --no-editor

python -m triageflow evidence attach --uart-log "$TRIAGEFLOW_ROOT/uart.log"
python -m triageflow evidence hunt

python -m triageflow facts add --text "panic observed during flow" --evidence E001
python -m triageflow hypotheses add \
  --hypothesis "watchdog reset triggers reboot" \
  --evidence E001 \
  --test "print reset cause / wdt reason"

python -m triageflow direction-build --overwrite --top-n 1
python -m triageflow validate
python -m triageflow status

Profiles

List built-in profiles:

python -m triageflow profile list

Current profiles:

• embedded_system_v1: stability/power/bt/charging (UART-first)
• design_system_v1: software design decisions
• product_definition_v1: product definition decisions

Expert Constraints (dianoia integration)

Use a dianoia distilled expert profile to inject domain expertise into the workflow. The expert profile acts as a continuous supervisor — its constraints apply to every decision throughout the workflow, not just during review.

kitchen init --profile design_system_v1 --expert ~/dianoia-experts/ai-product-architect

This generates a CLAUDE.md in the workspace root with all expert constraints grouped by domain layer (identity, goals, methods, values). The AI agent reads these as authoritative guardrails: every hypothesis, direction, and decision must respect the expert's knowledge.

For Agents

See AGENTS.md.

Developer

python -m pip install -e ".[dev]"
python -m pytest -q
python -m triageflow acceptance run