Kanban Run

Auto-Trigger Rules

ALWAYS invoke this skill (without waiting for /kanban-run) when:

1. User mentions a kanban task ID and requests implementation:

   • "implement task #NNN" / "build task NNN" / "do NNN" / "run NNN"
   • Korean equivalents: "태스크 NNN 구현해줘" / "NNN 해줘" / "NNN 번 작업해줘"
   • Any message pairing a task number with implement / build / work on / do

2. Claude has proposed implementing a specific kanban task and the user confirms:

   • Pattern: Claude says "Shall I implement task #NNN [title]?" → User replies "yes", "ok", "go", "do it", "응", "해줘", "그래", "ㅇㅇ"
   • This confirmation must trigger /kanban-run <ID> automatically — do not implement manually

3. User says "next task" / "continue" / "다음 태스크 해줘" when a task is in progress:

   • Fetch board context first, identify next todo task, then run it

When auto-triggered: extract task ID and call /kanban-run <ID> — never implement code manually and patch kanban state afterward.

Shared context: read ../kanban/shared.md for DB path, pipeline levels, status transitions, DB operations, error handling, and agent context flow. Safety principles: read ../kanban/principles.md — mandatory, not optional. Schema: read ../kanban/schema.md for full DB schema, column descriptions, and JSON field formats.

Commands

In Codex environments, this skill may be invoked directly as a slash command text such as $kanban-run <ID> or $kanban-run <ID> --auto.

/kanban-run step <ID> — Single Step

Execute only the next pipeline step then exit. Same logic as /kanban-run but no loop.

/kanban-run <ID> [--auto] — Run Full Pipeline

Default: pause for user confirmation at Plan Review and Impl Review approvals. --auto: fully automatic (circuit breaker still fires).

Orchestration Loop (Level-Aware)

L1 Quick:
  todo → Worker(builder) implements → commit → done

L2 Standard:
  todo → Plan Agent(planner) → impl (skip plan_review)
  impl → Worker(builder) + TDD Tester(shield) → impl_review
  impl_review → Code Review → [user confirm] → commit → done / reject → impl

L3 Full:
  todo → Plan Agent(planner) → plan_review
  plan_review → Review Agent(critic) → [user confirm: y/c/n] → impl / ceo-review / reject→plan
    └─ [c] CEO Review: product angle check → update plan → back to plan_review
  impl → Worker(builder) + TDD Tester(shield) → impl_review
  impl_review → Code Review(inspector) → [user confirm] → test / reject → impl
  test → Test Runner(ranger) → pass → commit → done / fail → impl

Circuit breaker: plan_review_count > 3 OR impl_review_count > 3 → stop, ask user

CEO Review (L3 plan_review only)

When the user selects [c] at the plan_review confirmation prompt, run a CEO-perspective analysis inline before proceeding to impl. Not a separate agent — run as a structured prompt to the current model:

Adopt the perspective of a skeptical product founder reviewing this plan.
Ask:
  (1) Is this feature actually necessary, or can the need be met more simply?
  (2) Does this align with the project's stated purpose? [load from project brief]
  (3) Is there a 10x simpler implementation that solves 80% of the problem?
  (4) What might we regret about this decision in 6 months?
Output: bullet list of concerns, or "No concerns — looks right-sized."

After CEO review output, present: [y] proceed to impl / [r] revise plan / [n] reject

Read the task's level field first to determine which steps to execute.

Model Routing (Provider-Aware)

Resolve real model names from ../kanban/models.json using provider:

• KANBAN_MODEL_PROVIDER env var if set (claude or codex)
• else codex when CODEX_* env is present
• else claude when CLAUDE_* env is present
• else claude when .claude/ exists
• else codex when .codex/ exists
• else default_provider from models.json

For Codex, the router should prefer the higher-capability entries in models.json for the full kanban-run pipeline.

MODEL_PROVIDER=${KANBAN_MODEL_PROVIDER:-}
if [ -z "$MODEL_PROVIDER" ] && [ -n "${CODEX_THREAD_ID:-}${CODEX_CI:-}" ]; then MODEL_PROVIDER=codex; fi
if [ -z "$MODEL_PROVIDER" ] && [ -n "${CLAUDE_PROJECT_DIR:-}${CLAUDECODE:-}" ]; then MODEL_PROVIDER=claude; fi
if [ -z "$MODEL_PROVIDER" ] && [ -d .claude ]; then MODEL_PROVIDER=claude; fi
if [ -z "$MODEL_PROVIDER" ] && [ -d .codex ]; then MODEL_PROVIDER=codex; fi

read_model() {
  local key="$1"
  python3 - "$MODEL_PROVIDER" "$key" <<'PY'
import json, pathlib, sys
p = pathlib.Path("../kanban/models.json")
d = json.loads(p.read_text())
provider = sys.argv[1] or d["default_provider"]
key = sys.argv[2]
print(d["providers"][provider][key])
PY
}

read_effort() {
  local key="$1"
  python3 - "$MODEL_PROVIDER" "$key" <<'PY'
import json, pathlib, sys
p = pathlib.Path("../kanban/models.json")
d = json.loads(p.read_text())
provider = sys.argv[1] or d["default_provider"]
key = sys.argv[2]
print(d.get("reasoning_effort", {}).get(provider, {}).get(key, ""))
PY
}

MODEL_PLANNER=$(read_model planner)
MODEL_CRITIC=$(read_model critic)
MODEL_BUILDER=$(read_model builder)
MODEL_SHIELD=$(read_model shield)
MODEL_INSPECTOR=$(read_model inspector)
MODEL_RANGER=$(read_model ranger)
EFFORT_PLANNER=$(read_effort planner)
EFFORT_CRITIC=$(read_effort critic)
EFFORT_BUILDER=$(read_effort builder)
EFFORT_SHIELD=$(read_effort shield)
EFFORT_INSPECTOR=$(read_effort inspector)
EFFORT_RANGER=$(read_effort ranger)

Implementation

# 1. Read current task state (status + level only)
TASK=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$ID?project=$PROJECT&fields=status,level")
STATUS=$(echo "$TASK" | jq -r '.status')

# 2. Dispatch agent (see Agent Dispatch below)
# 3. After agent: append to agent_log (see schema.md for format)
# 4. Re-read state, loop until done or circuit breaker

Agent Nicknames & Identity

Each agent has a fixed nickname used consistently across all records. The task card becomes a work log — every field and every log entry is signed.

See ../kanban/schema.md for JSON formats and the Signature Header Rule.

Agent Dispatch

Template files are at ../kanban/templates/.

Agent minimum fields (fetch only what each agent needs):

Dispatch procedure — execute in this order for every agent:

⓪ Fetch project brief (once per pipeline run, cache for all agents)
   PROJECT_DATA = curl GET /api/projects/$PROJECT
   PROJECT_BRIEF = extract .brief field (empty string if null or project not found)
   This is injected into every agent template via <project_brief> placeholder.

⓪ʙ Resolve dependencies & review feedback (once per pipeline run, cache for all agents)

   **Parse dependencies from description:**
   ```bash
   # Extract dependency IDs from description (case-insensitive)
   DESCRIPTION=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$ID?project=$PROJECT&fields=description" | jq -r '.description // ""')
   DEP_IDS=$(echo "$DESCRIPTION" | grep -ioP 'Depends on:\s*\K#\d+(?:,\s*#\d+)*' | grep -oP '\d+' || true)

Circular dependency check: If $ID (current task) appears in any dependency's own Depends on: line, emit error and abort:

for DEP_ID in $DEP_IDS; do
  DEP_TASK=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$DEP_ID?project=$PROJECT&fields=title,status,description,decision_log,implementation_notes")
  HTTP_CODE=$(echo "$DEP_TASK" | jq -r '.id // empty')
  if [ -z "$HTTP_CODE" ]; then
    echo "WARNING: dependency #$DEP_ID not found (404), skipping"
    continue
  fi
  DEP_DESC=$(echo "$DEP_TASK" | jq -r '.description // ""')
  if echo "$DEP_DESC" | grep -iqP "Depends on:.*#$ID\\b"; then
    echo "ERROR: circular dependency detected — #$ID ↔ #$DEP_ID. Aborting."
    exit 1
  fi
  # Cache: DEPS[$DEP_ID] = { title, status, decision_log, implementation_notes }
done

Build per-agent dependency context string: For each cached dependency, assemble context based on the current agent:

• Planner: decision_log (500 chars) + implementation_notes (500 chars)
• Builder: implementation_notes (500 chars)
• Inspector: decision_log (300 chars)

Truncation: if field length > limit, take first N chars + ...[truncated]. If dep status != done: prepend [IN PROGRESS] warning to that dep's block. If no dependencies: DEPS_CONTEXT="" (empty string — placeholder removed cleanly).

Format per dependency:

### #<DEP_ID>: <title> [<status>]
[IN PROGRESS]

**Decision Log:**
<truncated decision_log>

**Implementation Notes:**
<truncated implementation_notes>

Extract review feedback for re-runs:

# Critic feedback (for Planner re-run)
CRITIC_FEEDBACK=""
PLAN_REVIEW_COMMENTS=$(echo "$TASK" | jq -r '.plan_review_comments // ""')
if [ -n "$PLAN_REVIEW_COMMENTS" ] && [ "$PLAN_REVIEW_COMMENTS" != "null" ]; then
  CRITIC_FEEDBACK=$(echo "$PLAN_REVIEW_COMMENTS" | python3 -c "
import sys, json
data = json.load(sys.stdin)
if isinstance(data, list) and len(data) > 0:
  print(data[-1].get('comment', ''))
")
fi

# Inspector feedback (for Builder re-run)
INSPECTOR_FEEDBACK=""
REVIEW_COMMENTS=$(echo "$TASK" | jq -r '.review_comments // ""')
if [ -n "$REVIEW_COMMENTS" ] && [ "$REVIEW_COMMENTS" != "null" ]; then
  INSPECTOR_FEEDBACK=$(echo "$REVIEW_COMMENTS" | python3 -c "
import sys, json
data = json.load(sys.stdin)
if isinstance(data, list) and len(data) > 0:
  print(data[-1].get('comment', ''))
")
fi

① Read task fields (use per-agent fields to minimize token usage)

Planner

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan_review_comments

Critic

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,decision_log,done_when

Builder

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,done_when,plan_review_comments,review_comments

Shield

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,implementation_notes

Inspector

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,done_when,implementation_notes

Ranger

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,implementation_notes Extract only the fields listed above for each agent

② Mark agent as active curl PATCH /api/task/$ID → { "current_agent": "" }

③ Read template file Read tool: ../kanban/templates/.md

④ Fill placeholders in template Replace every occurrence of: → actual task ID → actual project name → project brief from step ⓪ (empty string if not set) → task title → task description (requirements) → plan field value → decision_log field value → done_when field value → implementation_notes field value → plan_review_comments field value → per-agent dep context from step ⓪ʙ (empty string if none) → latest plan_review_comments comment (empty if first run) → latest review_comments comment (empty if first run) → current UTC time (ISO 8601) → $MODEL_PLANNER → $MODEL_CRITIC → $MODEL_BUILDER → $MODEL_SHIELD → $MODEL_INSPECTOR → $MODEL_RANGER → $EFFORT_PLANNER → $EFFORT_CRITIC → $EFFORT_BUILDER → $EFFORT_SHIELD → $EFFORT_INSPECTOR → $EFFORT_RANGER

Recommended helper script:

PROMPT=$(python3 ../kanban/scripts/render_agent_prompt.py \
  --template ../kanban/templates/<agent>.md \
  --models ../kanban/models.json \
  --provider "$MODEL_PROVIDER" \
  --set ID="$ID" \
  --set PROJECT="$PROJECT" \
  --set project_brief="$PROJECT_BRIEF" \
  --set title="$TITLE" \
  --set description="$DESCRIPTION" \
  --set plan="$PLAN" \
  --set decision_log="$DECISION_LOG" \
  --set done_when="$DONE_WHEN" \
  --set implementation_notes="$IMPLEMENTATION_NOTES" \
  --set plan_review_comments="$PLAN_REVIEW_COMMENTS" \
  --set dependencies_context="$DEPS_CONTEXT" \
  --set critic_feedback="$CRITIC_FEEDBACK" \
  --set inspector_feedback="$INSPECTOR_FEEDBACK" \
  --set TIMESTAMP="$TIMESTAMP")

If a field is missing, pass empty string (--set key=""). Use --strict only when every unresolved <...> token should be treated as an error.

⑤ Launch Task tool with filled prompt If MODEL_PROVIDER is codex: Task( subagent_type = "general-purpose", model = "", model_reasoning_effort= "", prompt = )

Otherwise (claude): Task( subagent_type = "general-purpose", model = "", prompt = )

⑥ After Task completes — append signed entry to agent_log (use schema.md › "Appending to agent_log" snippet, set agent=, model=, message=)

After Builder + Shield both complete, move to `impl_review`:
```bash
curl -s "${AUTH_HEADER[@]}" -X PATCH "$BASE_URL/api/task/$ID?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d '{"status": "impl_review", "current_agent": null}'

Default mode: after plan_review and impl_review agents complete, ask user with AskUserQuestion to accept/reject before advancing. Auto mode (--auto): auto-accept the agent's decision.

→ Done Transition (all levels)

# 1. Commit pending changes
if [ -n "$(git status --porcelain 2>/dev/null)" ]; then
  git add -A
  git commit -m "feat: <TITLE> [kanban #<ID>]"
fi
COMMIT_HASH=$(git rev-parse --short HEAD 2>/dev/null || echo "no-git")

# 2. Move to done
curl -s "${AUTH_HEADER[@]}" -X PATCH "$BASE_URL/api/task/$ID?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d '{"status": "done"}'

# 3. Record commit hash in notes
curl -s "${AUTH_HEADER[@]}" -X POST "$BASE_URL/api/task/$ID/note?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d "{\"content\": \"Commit: $COMMIT_HASH\"}"

If no commits yet, skip note or record "Commit: (none)".

/kanban-run review <ID> — Code Review

Trigger Code Review agent for a task in impl_review status (same as impl_review step).