workflow-start

name	workflow-start
description	[Skill Management] Use when starting a detected workflow, initializing workflow state, or activating a workflow sequence.

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

Quick Summary

Goal: Detect user intent → present catalog/custom options → activate with full task tracking plan.

Workflow:

1. Detect — Match prompt against workflow catalog; identify best catalog workflow + optional custom pipeline
2. Ask — Use a direct user question to present up to THREE options before doing anything else
3. Activate — Create ALL task tracking items for chosen sequence; mark first in_progress

Key Rules:

• MUST ATTENTION always call a direct user question before activating — NEVER auto-activate or skip the confirmation step
• Present THREE options: A) Activate [Workflow] (Recommended) | B) Custom Pipeline: [step → ...] | C) Execute directly
• Propose Custom Pipeline when no catalog workflow is a strong fit (>80% steps relevant = use catalog)
• workflows.json workflows field is an OBJECT — use workflows[workflowId], NEVER .find() or [index]
• Create ALL task tracking items BEFORE marking the first task in_progress — batch creation, then execute
• NEVER mark a task completed without invoking its skill invocation — skip = in_progress + comment, not delete
• ALWAYS check context for ## Workflow Catalog first (Tier 1) — NEVER read workflows.json directly when catalog is in context
• If another workflow is active, it auto-switches (ends current, starts new) — no manual cleanup needed

NOT for: Manual step execution (follow task tracking items), workflow design (use planning), catalog management.

Related: $workflow-start <workflowId> | Hook: workflow-step-tracker.cjs | Hook: workflow-router.cjs

---

Custom Pipeline Option

When the prompt doesn't cleanly match a single catalog workflow — or combining steps from multiple workflows serves the request better — the AI MAY propose a Custom Pipeline alongside the catalog option.

When to propose

Condition	Example
No catalog workflow matches well	"Review hook changes and update skill docs" — spans review + docs
Best-match has significant unnecessary steps	Quick investigate + fix, but bugfix includes full TDD + integration cycle
Prompt combines 2+ workflow domains	"Audit performance and write integration tests for the slow query"
User explicitly requests a step sequence	"Just run scout, plan, and cook — nothing else"

Do NOT propose when a catalog workflow is a strong match (>80% of its steps are relevant). Catalog workflows encode validated best-practice sequences — prefer them.

How to build

1. Valid steps only — Use only keys from commandMapping in workflows.json. No invented step names.
2. Logical order — Investigate → Plan → Implement → Test. Never reverse dependency order.
3. Minimal — Include only steps the prompt needs. No "just in case" additions.
4. Name it — Short descriptive name: "Quick Fix + Docs", "Audit + Test Coverage".

How to present (ask the user directly format)

Show full step sequences for ALL options so the user compares scope:

Option A — Activate "Bug Fix" workflow (Recommended)
  Steps: $scout → $investigate → $debug-investigate → $plan-hard → $fix → $prove-fix → $test → ...

Option B — Custom Pipeline: "Quick Fix + Docs"
  Steps: $scout → $investigate → $fix → $docs-update
  Rationale: Prompt targets a known location — full TDD cycle is over-engineered here.

Option C — Execute directly without workflow

Rules:

• Always show full step list per option
• One-sentence AI rationale for the custom pipeline
• Catalog workflow = "(Recommended)" unless custom pipeline confidence is clearly higher
• NEVER present custom pipeline as the only option — always include the catalog option

Task creation for Custom Pipeline

Same 1:1 protocol — one task tracking per step. Use [Custom] prefix to distinguish from catalog tasks:

Task tracking: subject="[Custom] /{step-name} — {brief description}", description="Custom pipeline step N/{total}.", activeForm="Executing /{step-name}"

---

Workflow Lookup — Token-Efficient (3-Tier Strategy)

ALWAYS try tiers in order — stop at first success.

Tier 1: Context (FREE — no file reads)

The workflow catalog is already injected as ## Workflow Catalog in your context (injected by workflow-router.cjs on every UserPromptSubmit).

1. Search your context for ## Workflow Catalog
2. Find the line: **{workflowId}** — {name}
3. Read the NEXT line: Use: ... | Steps: /step1 → /step2 → ...
4. Parse the Steps: value — these ARE the slash commands for task tracking

Example: Steps: $scout → $plan-hard → $cook → $test → $workflow-end → Create 5 task tracking items for $scout, $plan-hard, $cook, $test, $workflow-end in order.

✅ Use Tier 1 for: all standard task tracking creation (no file reads needed) ⚠️ Use Tier 2 if: catalog not in context, OR you need preActions.injectContext

Tier 2: Targeted Grep (1 grep operation)

Use when catalog is absent from context OR preActions.injectContext is needed:

Grep: pattern='"<workflowId>":'  path='.claude/workflows.json'  context=35

Returns only that workflow's entry (~35 lines vs full file). Parse: sequence array → step IDs → resolve via commandMapping.

Tier 3: Minimal Read (last resort — avoid)

Only if Tier 1 and Tier 2 both fail:

Read '.claude/workflows.json' lines 1-15    ← commandMapping only
Then Grep '"<workflowId>":' context=30

NEVER read the full file — it is large and wastes tokens.

---

After Activation — Task Creation Protocol (ZERO TOLERANCE)

FIRST action after activation: create EXACTLY one task tracking for EACH entry in the workflow's sequence array.

How to read workflows.json — CRITICAL SCHEMA

workflows.json is a JSON OBJECT, not an array. Most common AI mistake.

{
  "commandMapping": { <stepId>: { "claude": "/cmd", "copilot": "/cmd" } },
  "settings":       { ... },
  "workflows":      { <workflowId>: WorkflowEntry }   ← OBJECT, keyed by ID
}

Lookup algorithm:

workflow = workflows[workflowId]           // key lookup — NOT .find(), NOT [index]
steps    = workflow.sequence               // array of step ID strings
// resolve slash command:
slashCmd = commandMapping[stepId].claude   // commandMapping["scout"].claude → "$scout"

WorkflowEntry fields:

Field	Type	Notes
name	string	Display name
confirmFirst	boolean	Prompt user before starting
sequence	string[]	Ordered step IDs — SOLE source of truth
whenToUse / whenNotToUse	string	Natural language intent matching
preActions	object	Optional injectContext / readFiles

FORBIDDEN (common mistakes):

// ❌ WRONG
workflows.find(w => w.id === workflowId)
workflows[0]

// ✅ CORRECT
workflows[workflowId]
Object.keys(workflows)   // list all IDs

Task creation steps

1. Tier 1 first (no file read): Search context for ## Workflow Catalog → find **{workflowId}** → parse Steps: line → slash commands are ready to use
2. Tier 2 if needed: Grep .claude/workflows.json --pattern '"<workflowId>":' --context 35 → parse sequence + commandMapping
3. Create one task tracking per step IN ORDER

See Workflow Lookup — Token-Efficient (3-Tier Strategy) above for full lookup rules and fallback chain.

Task format:

Task tracking: subject="[Workflow] /{step-name} — {brief description}", description="Workflow step N/{total}. {conditional note}", activeForm="Executing /{step-name}"

Rules (NON-NEGOTIABLE):

• 1:1 mapping — each sequence entry = exactly one task. No consolidation, no invented tasks.
• Conditional steps still get tasks — add to description: "Conditional — skip if reviews pass"
• Recursive self-calls get tasks — e.g., [Workflow] $workflow-review-changes — Recursive re-review (conditional)
• Count verification — after creation: task count == len(sequence). Fix mismatch before proceeding.

Create ALL tasks first → then TaskUpdate first task to in_progress.

---

Step Execution Protocol

Per step: TaskUpdate in_progress → invoke skill invocation → complete skill → TaskUpdate completed.

• Completing a task without invoking its skill invocation = workflow violation
• Validation gates ($plan-validate, $plan-review, $why-review) MUST use a direct user question — never auto-approve
• To skip a conditional step: TaskUpdate in_progress → comment "Skipped — {reason}" → TaskUpdate completed. Never delete.

---

Workflow-in-Workflow Gate (HARD GATE — NO EXCEPTIONS)

Some workflow steps ARE themselves full workflows. Running them inline causes the parent session to absorb the entire nested workflow's tool calls, file reads, and sub-agent reports — guaranteed context overflow on long sequences.

Steps requiring sub-agent delegation (hard gate):

Step	Workflow activated	Steps	Agent type
$workflow-review-changes	review-changes	16	code-reviewer
$workflow-review	review	14	code-reviewer

Protocol when these steps appear in the active workflow sequence:

1. NEVER invoke via inline skill invocation call
2. Spawn via spawn_agent tool: agent_type: "code-reviewer"
3. Agent prompt must include: current git diff context + feature/task description
4. Sub-agent runs the full nested workflow in its isolated context
5. Return ONLY SYNC:subagent-return-contract summary — write full findings to plans/reports/
6. Main agent reads plans/reports/ file only when resolving specific blockers

The workflow-step-tracker.cjs PostToolUse hook injects the ⚠️ [WORKFLOW-IN-WORKFLOW GATE] warning automatically when the next step is one of the above.

---

IMPORTANT MANDATORY Steps: detect-workflow -> analyze-best-match -> ask-user-workflow-choice -> activate-workflow -> create-task-tracking -> execute-sequence

IMPORTANT MANDATORY Steps: detect-workflow -> analyze-best-match -> ask-user-workflow-choice -> activate-workflow -> create-task-tracking -> execute-sequence

[MANDATORY] task tracking FIRST — break every workflow into tasks before any action. NEVER skip. [MANDATORY] a direct user question ALWAYS — present 3 options, NEVER auto-activate. [MANDATORY] skill invocation REQUIRED per step — NEVER mark a task completed without invoking it.

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

Incremental Result Persistence — MANDATORY for all sub-agents or heavy inline steps processing >3 files.

1. Before starting: Create report file plans/reports/{skill}-{date}-{slug}.md
2. After each file/section reviewed: Append findings to report immediately — never hold in memory
3. Return to main agent: Summary only (per SYNC:subagent-return-contract) with Full report: path
4. Main agent: Reads report file only when resolving specific blockers

Why: Context cutoff mid-execution loses ALL in-memory findings. Each disk write survives compaction. Partial results are better than no results.

Report naming: plans/reports/{skill-name}-{YYMMDD}-{HHmm}-{slug}.md

Sub-Agent Return Contract — When this skill spawns a sub-agent, the sub-agent MUST return ONLY this structure. Main agent reads only this summary — NEVER requests full sub-agent output inline.

## Sub-Agent Result: [skill-name]

Status: ✅ PASS | ⚠️ PARTIAL | ❌ FAIL
Confidence: [0-100]%

### Findings (Critical/High only — max 10 bullets)

- [severity] [file:line] [finding]

### Actions Taken

- [file changed] [what changed]

### Blockers (if any)

- [blocker description]

Full report: plans/reports/[skill-name]-[date]-[slug].md

Main agent reads Full report file ONLY when: (a) resolving a specific blocker, or (b) building a fix plan. Sub-agent writes full report incrementally (per SYNC:incremental-persistence) — not held in memory.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

MUST ATTENTION call a direct user question BEFORE activating — present all THREE options (catalog | custom pipeline | execute directly). Never auto-activate. MUST ATTENTION workflows is an OBJECT — workflows[workflowId], NEVER .find() / [index] / .forEach() MUST ATTENTION create ALL task tracking items for the full sequence BEFORE marking the first task in_progress MUST ATTENTION never mark a task completed without invoking its skill invocation — skip means comment + completed, not delete MUST ATTENTION custom pipeline steps must be valid commandMapping keys — never invent step names MUST ATTENTION use Tier 1 context parse FIRST — check ## Workflow Catalog in context before any file read

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using task tracking.

[IMPORTANT] Analyze how big the task is and break it into many small todo tasks systematically before starting — this is very important.

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

1. DETECT: Match prompt against workflow catalog
2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better
3. ASK (REQUIRED FORMAT): Use a direct user question with this structure:
   • Question: "Which workflow do you want to activate?"
   • Option 1: "Activate [BestMatch Workflow] (Recommended)"
   • Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)
4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually
5. CREATE TASKS: task tracking for ALL workflow steps
6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows.

Learned Lessons

Lessons Learned

[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.

Quick Summary

Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.

Top Rules (apply always):

• MUST ATTENTION verify ALL preconditions (config, env, DB names, DI regs) BEFORE code-layer hypothesis
• MUST ATTENTION fix responsible layer — NEVER patch symptom sites with caller-specific defensive code
• MUST ATTENTION use ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTask
• MUST ATTENTION name by PURPOSE not CONTENT — adding member forces rename = abstraction broken
• MUST ATTENTION persist sub-agent findings incrementally after each file — NEVER batch at end
• MUST ATTENTION Windows bash: verify Python alias (where python/where py) — NEVER assume python/python3 resolves

---

Debugging & Root Cause Reasoning

• [2026-04-11] Holistic-first: verify environment before code. Failure → list ALL preconditions (config, env vars, DB names, endpoints, DI regs, credentials, permissions, data prerequisites) → verify each via evidence (grep/cat/query) BEFORE code-layer hypothesis. Worst rabbit holes: diving nearest layer while bug sits elsewhere — e.g., hours debugging "sync timeout", real cause: test appsettings pointing wrong DB. Cheapest check first.
• [2026-04-01] Ask "whose responsibility?" before fixing. Trace: bug in caller (wrong data) or callee (wrong handling)? Fix responsible layer — NEVER patch symptom site masking real issue.
• [2026-04-01] Trace data lifecycle, not error site. Follow data: creation → transformation → consumption. Bug usually where data created wrong, not consumed.
• [2026-04-01] Code is caller-agnostic. Functions/handlers/consumers don't know who invokes them. Comments/guards/messages describe business intent — NEVER reference specific callers (tests, seeders, scripts).

Architecture Invariants

• [2026-03-31] ParallelAsync + repo/UoW MUST use ExecuteInjectScopedAsync, NEVER ExecuteUowTask. ExecuteUowTask creates new UoW but reuses outer DI scope (same DbContext) — parallel iterations sharing non-thread-safe DbContext silently corrupt data. ExecuteInjectScopedAsync creates new UoW + new DI scope (fresh repo per iteration).
• [2026-03-31] Bus message naming MUST include service name prefix — core services NEVER consume feature events. Prefix declares schema ownership (AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) are leaders. Feature services (Growth, Talents) sending to core MUST use {CoreServiceName}...RequestBusMessage — never define own event for core to consume.

Naming & Abstraction

• [2026-04-12] Name PURPOSE not CONTENT — "OrXxx" anti-pattern. HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what it guards. Add role → rename = broken abstraction. Rule: names express DOES/GUARDS, not CONTAINS. Test: adding/removing member forces rename? YES = content-driven = bad → rename to purpose (e.g., HrOperationsAccessPolicy). Nuance: "Or" fine in behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.

Environment & Tooling

• [2026-04-20] Windows bash: NEVER assume python/python3 resolves — verify alias first. Python may not be in bash PATH under those names. Check: where python / where py. Prefer py (Windows Python Launcher) for one-liners, node if JS alternative exists.

Test-specific lessons → docs/project-reference/integration-test-reference.md Lessons Learned section. Production-code anti-patterns → docs/project-reference/backend-patterns-reference.md Anti-Patterns section. Generic debugging/refactoring reminders → System Lessons in .claude/hooks/lib/prompt-injections.cjs.

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Closing Reminders

• IMPORTANT MUST ATTENTION holistic-first: verify ALL preconditions (config, env, DB names, endpoints, DI regs) BEFORE code-layer hypothesis — cheapest check first
• IMPORTANT MUST ATTENTION fix responsible layer — NEVER patch symptom site; trace caller (wrong data) vs callee (wrong handling), fix root owner
• IMPORTANT MUST ATTENTION parallel async + repo/UoW → ALWAYS ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption)
• IMPORTANT MUST ATTENTION bus message prefix = schema ownership; feature services NEVER define events for core services — use {CoreServiceName}...RequestBusMessage
• IMPORTANT MUST ATTENTION name by PURPOSE — adding/removing member forces rename = broken abstraction
• IMPORTANT MUST ATTENTION sub-agents MUST write findings after each file/section — NEVER batch all findings into one final write
• IMPORTANT MUST ATTENTION Windows bash: NEVER assume python/python3 resolves — run where python/where py first, use py launcher or node

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn.
6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead.
7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.