engineering-workflow

name	engineering-workflow
description	Micro-agent system for engineering architecture decisions across DB, BE, IF, SE domains. Routes queries to specialized micro agents for deep technical analysis. Activated by keywords: "db architecture", "storage engine", "index design", "query optimization", "concurrency", "isolation level", "schema design", "replication", "sharding", "consistency model", "engineering workflow", "architecture decision".
argument-hint	[query | analyze | compare | recommend] [--domain db|be|if|se] [--depth shallow|deep]
user-invocable	true
allowed-tools	["Read","Grep","Glob","Bash","Write","Edit","Task"]

Engineering Workflow — Micro-Agent Orchestration System

A 3-tier micro-agent system that routes engineering architecture queries to specialized domain agents, resolves cross-domain constraints, and synthesizes unified recommendations.

Role

A 3-tier micro-agent orchestration system for engineering architecture decisions spanning four major systems: DB (Database), BE (Backend), IF (Infrastructure), and SE (Security).

Architecture Overview

                         Tier 1: Gateway Router (this SKILL.md)
                                    |
                    ┌───────────────┼───────────────┐
                    |               |               |
               Tier 2: System Orchestrators
               ┌────┐  ┌────┐  ┌────┐  ┌────┐
               │ DB │  │ BE │  │ IF │  │ SE │
               └──┬─┘  └──┬─┘  └──┬─┘  └──┬─┘
                  |        |        |        |
               Tier 3: Micro Agents (domain-specific)
               ┌─────────────────────────────┐
               │ A: Storage  D: API Design   │
               │ B: Query    E: Concurrency  │
               │ C: Schema   F: Networking   │
               │ ...         ...             │
               └─────────────────────────────┘

Core Principles

1. Constraint-first synthesis: Agents declare constraints; conflicts are detected and resolved before output
2. Deterministic fast-path: Use classify-query.sh for unambiguous queries; reserve LLM classification for edge cases
3. Graceful degradation: If an agent fails or times out, return partial results with clear warnings

---

Routing Table

System Detection

System	Keywords	Orchestrator
DB	database, storage engine, index, query optimization, schema, replication, sharding, partition, consistency model, isolation level, MVCC, WAL, B-tree, LSM, vacuum, ACID, DynamoDB, RCU, WCU, hot partition, adaptive capacity, throttling	agents/db-orchestrator.md
BE	backend, API design, service layer, concurrency, thread pool, connection pool, caching strategy, microservice, event-driven, CQRS, saga, domain model	agents/be-orchestrator.md
IF	infrastructure, deployment, container, kubernetes, CI/CD, load balancer, CDN, monitoring, observability, scaling, network topology, DNS, TLS	agents/if-orchestrator.md
SE	security, authentication, authorization, encryption, key management, RBAC, ABAC, OAuth, JWT, zero-trust, penetration, vulnerability, compliance	agents/se-orchestrator.md

SE Sub-Domain Detection (6 Clusters: A/Z/E/N/C/V)

Cluster	Sub-Domain	Code	Keywords	Agent
A Authentication	AuthN Flow Design	A1	authentication, OAuth2, OIDC, SAML, SSO, login flow, protocol selection	agents/se/a1-authn-flow-designer.md
A Authentication	Token Strategy	A2	JWT, refresh token, access token, token rotation, token storage, claims	agents/se/a2-token-strategist.md
A Authentication	Session Architecture	A3	session management, MFA, SSO federation, stateless, session fixation	agents/se/a3-session-architect.md
A Authentication	Credential Management	A4	bcrypt, argon2, passkey, WebAuthn, passwordless, credential rotation	agents/se/a4-credential-manager.md
Z Authorization	Access Model Selection	Z1	RBAC, ABAC, ReBAC, access control model, multi-tenant, permission model	agents/se/z1-access-model-selector.md
Z Authorization	Policy Design	Z2	OPA, Cedar, Casbin, policy engine, policy rule, policy test	agents/se/z2-policy-designer.md
Z Authorization	Permission Audit	Z3	least privilege, over-privilege, permission matrix, role explosion	agents/se/z3-permission-auditor.md
Z Authorization	Scope Architecture	Z4	OAuth scope, API permission, dynamic scope, consent, token-permission	agents/se/z4-scope-architect.md
E Encryption	Encryption Strategy	E1	encryption at-rest, in-transit, field-level, AES-256, ChaCha20	agents/se/e1-encryption-advisor.md
E Encryption	Key Lifecycle	E2	key rotation, HSM, Vault, KMS, key escrow, key distribution	agents/se/e2-key-lifecycle-planner.md
E Encryption	TLS Configuration	E3	TLS, mTLS, cipher suite, certificate chain, OCSP, certificate pinning	agents/se/e3-tls-configurator.md
E Encryption	Secret Management	E4	HashiCorp Vault, AWS Secrets Manager, secret rotation, dynamic secret	agents/se/e4-secret-manager.md
N Network Security	Header Hardening	N1	CORS, CSP, HSTS, X-Frame-Options, Referrer-Policy, security headers	agents/se/n1-header-hardener.md
N Network Security	WAF/Rate-Limiting	N2	WAF, rate limiting, IP filtering, DDoS, geo-blocking, ModSecurity	agents/se/n2-waf-rule-designer.md
N Network Security	API Gateway Security	N3	API gateway, auth delegation, request validation, throttling, API key	agents/se/n3-api-gateway-security.md
N Network Security	Input Sanitization	N4	SQL injection, XSS, path traversal, content-type validation, sanitization	agents/se/n4-input-sanitizer.md
C Compliance	Compliance Mapping	C1	SOC2, ISO27001, GDPR, PCI-DSS, compliance framework, cross-mapping	agents/se/c1-compliance-mapper.md
C Compliance	Audit Trail Design	C2	audit logging, event schema, append-only, WORM, tamper detection	agents/se/c2-audit-trail-designer.md
C Compliance	Zero-Trust Planning	C3	zero-trust, microsegmentation, device trust, BeyondCorp, continuous verification	agents/se/c3-zero-trust-planner.md
C Compliance	Privacy Engineering	C4	GDPR data subject, consent management, PII, data masking, DPIA	agents/se/c4-privacy-engineer.md
V Vulnerability	Threat Modeling	V1	STRIDE, PASTA, attack tree, threat scenario, attack surface	agents/se/v1-threat-modeler.md
V Vulnerability	OWASP Audit	V2	OWASP Top 10, injection, XSS, auth flaw, SSRF, deserialization	agents/se/v2-owasp-auditor.md
V Vulnerability	Pentest Strategy	V3	penetration test, black-box, white-box, Burp, ZAP, Nuclei	agents/se/v3-pentest-strategist.md
V Vulnerability	Supply Chain Audit	V4	SCA, SBOM, license compliance, CVE, dependency vulnerability, Sigstore	agents/se/v4-supply-chain-auditor.md

DB Sub-Domain Detection (A-F)

Sub-Domain	Code	Keywords	Agents
Storage Engine	A	storage engine, B-tree, LSM-tree, page layout, WAL, buffer pool, compaction, write amplification	agents/db/a1-engine-selector.md, agents/db/a2-compaction-strategist.md
Index & Query Plan	B	query plan, explain analyze, index scan, seq scan, join strategy, cost estimation, query rewrite, statistics	agents/db/b1-index-architect.md, agents/db/b2-join-optimizer.md, agents/db/b3-query-plan-analyst.md
Concurrency & Locking	C	concurrency, isolation level, MVCC, locking, deadlock, optimistic, pessimistic, serializable, phantom read	agents/db/c1-isolation-advisor.md, agents/db/c2-mvcc-specialist.md, agents/db/c3-lock-designer.md
Schema & Normalization	D	schema design, normalization, denormalization, document model, embedding, referencing, access pattern	agents/db/d1-schema-expert.md, agents/db/d2-document-modeler.md, agents/db/d3-access-pattern-modeler.md
I/O & Buffer Management	E	page, buffer pool, WAL, write-ahead log, checkpoint, dirty page, flush, I/O optimization	agents/db/e1-page-optimizer.md, agents/db/e2-wal-engineer.md, agents/db/e3-buffer-tuner.md
Distributed & Replication	F	replication, failover, consensus, raft, paxos, sharding, partition, consistency, CAP theorem, dynamodb, rcu, wcu, hot partition, adaptive capacity, throttling, provisioned throughput, on-demand, TPS	agents/db/f1-replication-designer.md, agents/db/f2-consistency-selector.md, agents/db/f3-sharding-architect.md, agents/db/f4-dynamodb-throughput-optimizer.md

BE Sub-Domain Detection (4 Clusters: S/B/R/T)

Cluster	Sub-Domain	Code	Keywords	Agent
S Structure	Dependency Audit	S1	dependency violation, import direction, runtimeOnly, layer rule, module boundary	agents/be/s1-dependency-auditor.md
S Structure	DI Pattern	S2	Port design, Adapter injection, Constructor Injection, Stub pattern, DI	agents/be/s2-di-pattern-selector.md
S Structure	Architecture	S3	new module, naming convention, publisher vs producer, module layout, hexagonal	agents/be/s3-architecture-advisor.md
S Structure	Fitness Function	S4	ArchUnit, Konsist, checkTestNames, fitness function, CI automation	agents/be/s4-fitness-engineer.md
B Boundary	Context Classification	B1	external system, ACL vs Conformist, Semantic Gap, context mapping	agents/be/b1-context-classifier.md
B Boundary	ACL Design	B2	ACL design, Translator, Feign, testFixtures, anti-corruption	agents/be/b2-acl-designer.md
B Boundary	Event Architecture	B3	internal event, external event, SQS, event versioning, domain event	agents/be/b3-event-architect.md
B Boundary	Saga Coordination	B4	payment flow, compensation, Saga, Pivot step, compensable, retryable	agents/be/b4-saga-coordinator.md
R Resilience	Bulkhead	R1	bulkhead, Thread Pool, Semaphore, pool size, isolation	agents/be/r1-bulkhead-architect.md
R Resilience	Circuit Breaker	R2	Circuit Breaker, failureRate, slowCall, Resilience4j, half-open	agents/be/r2-cb-configurator.md
R Resilience	Retry/Timeout	R3	timeout budget, retry, fallback, idempotencyKey, backoff	agents/be/r3-retry-strategist.md
R Resilience	Observability	R4	monitoring, dashboard, tracing, Grafana, Prometheus, alert rule, micrometer	agents/be/r4-observability-designer.md
S Structure	Convention Verifier	S5	convention, code style, naming rule, JPA pattern, entity model, dynamic update	agents/be/s5-convention-verifier.md
B Boundary	Implementation Guide	B5	implementation guide, code pattern, feign client, translator code, saga implementation	agents/be/b5-implementation-guide.md
T Test	Test Guard	T1	Fixture Monkey, FakeRepository, test name byte, spyk, MockK, testcontainers	agents/be/t1-test-guard.md
T Test	Test Strategist	T2	test strategy, test technique, coverage target, property-based, contract test	agents/be/t2-test-strategist.md
T Test	Test Generator	T3	generate test, test generation, write test, focal context, type-driven	agents/be/t3-test-generator.md
T Test	Quality Assessor	T4	test quality, coverage, mutation, validation pipeline, gap analysis	agents/be/t4-quality-assessor.md

---

Execution Patterns

Four execution patterns exist: None (0 systems matched — falls through to LLM classification), Single-Domain (1 agent), Multi-Domain (2-3 agents, parallel dispatch), and Cross-System (multiple orchestrators + synthesizer).

For detailed flow diagrams and examples, see resources/orchestration-protocol.md § Pattern Examples.

---

Phase Flow

Pre-Flight Check (before Phase 0)

Run before any phase execution to ensure clean session state and detect reusable context.

1. Dependency check: Verify jq is available (command -v jq)
2. Interrupted session detection: Read ~/.claude/cache/engineering-workflow/progress.json
   • If status == "in_progress": previous session was interrupted
   • Archive the interrupted progress file and notify: "Previous session interrupted at phase {phase}. Starting fresh."
3. Session summary reuse: Read ~/.claude/cache/engineering-workflow/session-summary.json
   • If recent (< 30 min) and query is similar: display "Recent analysis available for reuse" with summary
   • Skip re-classification if the same query signature matches
4. Initialize progress: Write progress.json with {phase: "pre-flight", status: "in_progress"}
5. Run cleanup: Execute session cleanup (trim history, evict stale cache)

[engineering-workflow] Pre-Flight: deps=OK | prev_session={none|interrupted} | summary={available|none}

Phase 0: Query Classification

Resource: Read resources/routing-protocol.md when entering this phase.

1. Parse user input for explicit flags (--domain, --depth)
2. Run scripts/classify-query.sh "$QUERY" for keyword-based fast-path classification (2-phase: binary keywords → cross-keyword weighted scoring)
3. Progressive Classification: If session history exists within 30-minute window, augment confidence with prior_boost and suggest domain expansions based on transition patterns (see routing-protocol.md § Step 5.5)
4. Archetype Matching: If query matches a known archetype (e.g., multi-tenant-saas, event-driven-microservice), inject preset constraints from resources/constraints-archetypes.json
5. If confidence >= 0.85: proceed with fast-path result
6. LLM Verification (if needs_llm_verification == true, i.e., confidence > 0.0 AND < 0.85): Execute the lightweight LLM verification protocol defined in routing-protocol.md § Step 4.5:
   • Use the provided verification_prompt as-is (it is context-specific to system count)
   • Compare LLM answer against the keyword classification
   • If LLM agrees: boost confidence by +0.10 (capped at 0.85) and proceed
   • If LLM disagrees: adopt LLM classification, set classifier: "llm-verified", recalculate domains
   • Token cost: ~0.2K per verification (single-turn, no reference loading)
7. If confidence == 0.0 (no keywords matched): use full LLM classification (read routing-protocol.md for detailed algorithm)
8. Output: { systems: [...], domains: [...], pattern: "...", confidence: float, classifier: "...", prior_boost: float, suggested_expansions: [...], archetype_matched: [...], needs_llm_verification: bool, verification_prompt: string|null }

Progressive Classification rollback: Set EW_PROGRESSIVE_CLASSIFICATION=0 to disable.

Status Display:

[engineering-workflow] Phase: Classification | Pattern: {single|multi|cross} | Systems: {DB,BE,...}

Phase 1: Orchestrator Dispatch

Resource: Read resources/orchestration-protocol.md when entering this phase.

1. Based on classification result, identify required orchestrator(s)
2. Read the orchestrator .md file(s) from agents/
3. Construct Task prompt per orchestration-protocol.md template
4. For single-system: invoke one orchestrator Task
5. For cross-system: invoke multiple orchestrator Tasks in parallel
6. Run scripts/enforce-budget.sh <pattern> orchestrator-dispatch <output> to verify token budget before proceeding

Orchestrator Task prompt template:

You are the {system} System Orchestrator.

## Classification
{classification result from Phase 0}

## User Query
{original user query}

## Instructions
Read the relevant agent definition(s) from agents/{system}/ and dispatch sub-tasks.
Collect agent outputs and resolve intra-system constraints.
Return your analysis in the structured format defined in your orchestrator definition.

Phase 2: Agent Execution

BE Test Pipeline Status Display (when T2-T3-T4 loop is active):

[engineering-workflow] Phase: Test Pipeline | Loop: {n}/{max} | Coverage: {pct}% (target: {target}%)

Orchestrators handle this phase internally. Each orchestrator:

1. Reads the required agent .md file(s) from agents/{system}/
2. Constructs focused Task prompts for each agent
3. For multi-domain: dispatches agents in parallel via concurrent Task calls
4. Collects results and performs intra-system constraint merge
5. Returns structured output with constraints declared

Each agent determines its confidence score using the calibration rubric in resources/confidence-calibration.md (5-factor model: input completeness, specificity, evidence grounding, trade-off coverage, assumption count).

Agent Task prompt template:

You are the {domain} Micro Agent.

## Query Context
{focused sub-question extracted by orchestrator}

## Reference Material
{relevant excerpts loaded by orchestrator via Read with offset/limit}

## Output Requirements
1. Analysis: detailed technical analysis
2. Recommendation: concrete actionable recommendation
3. Constraints: declare any constraints your recommendation imposes on other domains
4. Trade-offs: explicit trade-off documentation
5. Confidence: score between 0.0–1.0 per `resources/confidence-calibration.md` rubric

Phase 2.5: Analysis Quality Gate

Resource: Read resources/analysis-audit-protocol.md when entering this phase.

This phase validates agent output quality before constraint resolution.

Tier	Steps	Additional Tokens
LIGHT	Confidence gating only	+0.3K
STANDARD	Confidence + Completeness + Feasibility	+1.5K
THOROUGH	All above + Dynamic Expansion via audit-reviewer agent	+3.5K

Steps: 0. Tier Determination: Run scripts/audit-analysis.sh tier <classification> <agent-count> — auto-selects LIGHT / STANDARD / THOROUGH based on system count, agent count, depth, and security keywords. Escalation is upward only (see auto-escalation rules below).

1. Budget Check: Run scripts/enforce-budget.sh <pattern> quality-gate <output> to verify token budget before audit
2. Confidence Gating (all tiers): Run scripts/audit-analysis.sh confidence per agent result

   • = 0.70: PASS

   • 0.50-0.69: PASS + warning
   • 0.30-0.49: Simplified re-dispatch (1 attempt)
   • < 0.30: Reject, orchestrator fallback
3. Completeness Audit (STANDARD+): 6-point checklist — split into deterministic (jq) and semantic (LLM):
   • Deterministic (jq via validate-agent-output.sh): automatically checked, no LLM cost
     • Point 2: 정량적 데이터 — validate-agent-output.sh detects number+unit patterns (ms, GB, %, TPS, etc.)
     • Point 3: Trade-off 문서화 — existing trade_offs array length check (>= 2 options)
     • Point 4: Constraint 선언 — existing constraints field presence check
   • Semantic (LLM evaluation, STANDARD+ only): evaluate each agent output against these 3 criteria:
     • Point 1: 맥락 반영 — Does the analysis address the user's specific context, not generic advice?
     • Point 5: Actionable 추천 — Is the recommendation concrete and implementable, not vague?
     • Point 6: 컨텍스트 인용 — Does the analysis reference key terms from the user's query?
   • LLM evaluation output: for each point, PASS or FAIL with one-line reason. If any FAIL: add warning to output
4. Feasibility Check (STANDARD+): Verify recommendations against constraints_used environment
5. Dynamic Expansion (THOROUGH only): Dispatch audit-reviewer agent for gap detection and expansion

Auto-escalation (upward only):

• 2+ agents with confidence < 0.50 → LIGHT→STANDARD
• Unexpected cross-system constraint → STANDARD→THOROUGH
• Security keywords in agent output → immediate THOROUGH

Phase 3: Constraint Resolution

Resource: Read resources/constraint-propagation.md when entering this phase.

1. Collect all constraint declarations from agents (including archetype-injected constraints)
2. Run scripts/resolve-constraints.sh to detect conflicts:
   • Tier 1 (Structural): Same target, different values — existing detection
   • Tier 2 (Semantic): Known incompatible pairs (e.g., LSM + low read latency) — detected via KNOWN_CONFLICT_PAIRS in _common.sh
3. If no conflicts: merge constraints into unified set
4. If conflicts detected:
   • For intra-system conflicts: orchestrator resolves using domain priority rules
   • For cross-system conflicts: escalate to synthesizer (Phase 4)
5. Orchestrators include all_declared_constraints (pre-resolution snapshot) for synthesizer transparency
6. Store resolved constraints in ~/.claude/cache/engineering-workflow/constraints.json

Phase 3.5: Contract Enforcement Gate

Resource: Reuse resources/analysis-audit-protocol.md (already loaded at Phase 2.5).

STANDARD+ tier only. Validates orchestrator output contracts before synthesis.

Steps:

1. Schema Contract Validation (STANDARD+): Run scripts/audit-analysis.sh orchestrator per orchestrator output
   • Validates required fields (system, status, guidance, recommendations, etc.)
   • Auto-fills defaults for non-critical missing fields with warnings
2. Priority Consistency Check (THOROUGH only): Verify intra-system conflict resolutions follow priority-matrix.md
3. Constraint Forwarding Completeness (THOROUGH only): Verify cross-system impacts are forwarded to unresolved_constraints

Phase 4: Synthesis (Cross-System Only)

Only activated for Pattern "cross" (cross-system) queries.

1. Run scripts/enforce-budget.sh <pattern> synthesis <output> to verify token budget before synthesis
2. Read agents/synthesizer.md
3. Pass all orchestrator outputs + resolved/conflicting constraints
4. Synthesizer produces:
   • Unified recommendation that respects all system constraints
   • Explicit documentation of cross-system trade-offs
   • Implementation priority ordering
   • Risk assessment for constraint violations

Phase 4.5: Synthesis Validation Gate

Resource: Reuse resources/analysis-audit-protocol.md (already loaded at Phase 2.5).

THOROUGH tier, cross-system pattern only. Validates synthesis output integrity.

Steps:

1. Coverage Check: Run scripts/audit-analysis.sh synthesis — verify all systems_analyzed are reflected in unified_recommendation
2. Ordering Validation: Verify implementation_order.depends_on references valid phases (topological sort consistency)
3. Risk-Rollback Completeness: Verify risk: "high" phases have rollback strategies defined
4. Confidence Floor: If confidence_assessment.overall is "low", add explicit caveat to output

Phase 5: Output Formatting

1. Run scripts/format-output.sh to structure the final output
2. Output format:

## Engineering Analysis: {query summary}

### Classification
- Pattern: {single|multi|cross}
- Systems: {DB, BE, ...}
- Domains: {A, C, ...}
- Depth: {shallow|deep}

### Analysis
{per-domain analysis sections}

### Recommendation
{unified recommendation}

### Constraints
{resolved constraint set}

### Trade-offs
| Option | Pros | Cons | Recommended When |
|--------|------|------|-----------------|

### Implementation Priority
1. {highest priority action}
2. {next action}
...

### Risk Assessment
| Risk | Impact | Likelihood | Mitigation |
|------|--------|------------|------------|

---

Execution Modes

Mode	Input Example	Behavior
Query (default)	"Should I use B-tree or LSM for writes?"	Full pipeline: Classify → Dispatch → Execute → Resolve → Format
Analyze	analyze: "our current sharding strategy"	Deep analysis without recommendation
Compare	compare: "PostgreSQL vs CockroachDB for multi-tenant"	Structured comparison with decision matrix
Recommend	recommend: "caching strategy for read-heavy API"	Recommendation-focused with implementation steps

Depth flag: --depth shallow (1 agent, ~3K) or --depth deep (all relevant agents, ~6-14K, default).

---

Resource Loading Instructions

Resources are loaded on-demand per phase. MUST NOT pre-load all resources.

Phase	Resource to Load	Trigger
Phase 0	resources/routing-protocol.md	Always at Phase 0 entry
Phase 1	resources/orchestration-protocol.md	Always at Phase 1 entry
Phase 1 (DB)	resources/db-orchestration-protocol.md	When DB system detected
Phase 1 (BE)	resources/be-orchestration-protocol.md	When BE system detected
Phase 1 (IF)	(stub — no dedicated protocol; uses general orchestration-protocol.md)	When IF system detected
Phase 1 (SE)	resources/se-orchestration-protocol.md	When SE system detected
Phase 2	resources/confidence-calibration.md	Loaded by orchestrators for agent confidence scoring
Phase 2.5	resources/analysis-audit-protocol.md	Always at Phase 2.5 entry (reused in 3.5, 4.5)
Phase 3	resources/constraint-propagation.md	Always at Phase 3 entry
Phase 3	resources/priority-matrix.md	When conflicts detected (reused in Phase 4)
Phase 4	resources/synthesis-protocol.md	Cross-system pattern only
Any	resources/error-playbook.md	On error occurrence

Agent definitions (loaded by orchestrators during Phase 2):

• Orchestrator .md files: loaded by Gateway Router in Phase 1
• Micro agent .md files: loaded by orchestrators in Phase 2
• agents/synthesizer.md: loaded by Gateway Router in Phase 4 (cross-system only)

Reference excerpts (loaded by agents during Phase 2):

• Agents may use Read with offset/limit to load relevant sections from large reference files
• Follow the large file loading rules: <=200 lines full read, 201-500 lines offset/limit, >500 lines Grep then Read

---

Constraint Propagation

Agents declare constraints (requires | recommends | prohibits | conflicts_with) in their output. Constraints flow upward through orchestrators → synthesizer for resolution. Hard constraints MUST be respected; soft constraints may be overridden with justification.

Schema, flow diagrams, and storage: resources/constraint-propagation.md

---

Token Budget Guidelines

Token budgets are guidelines, not hard limits. Exceeding the budget triggers reference excerpt truncation, not query failure.

Pattern	Agents	Budget	Audit	Total
Shallow	1	~3.5K	+0.3K (LIGHT)	~3.8K
Analysis only	1-4	~6K	+1.5K (STANDARD)	~7.5K
Implementation guide	3-6	~8K	+1.5K (STANDARD)	~9.5K
Test generation	3-5	~10K	+1.5K (STANDARD)	~11.5K
Full pipeline	6-10	~12K	+1.5K (STANDARD)	~13.5K
Cross-system	3-6	~15K	+3.5K (THOROUGH)	~18.5K
Cross-system (pruning)	3-6	~10K	+3.5K (THOROUGH)	~13.5K

Note: Budgets include ~20% contingency for complex queries requiring additional reference loading. Actual token usage is typically 10-20% below budget for standard queries.

Budget enforcement: Run scripts/enforce-budget.sh <pattern> <phase> <output> at phase transitions. Exits non-zero if estimated tokens exceed 120% of budget. Patterns: shallow, analysis, implementation, test, full, cross-system, cross-pruning.

Budget guidelines:

1. Orchestrators MUST use offset/limit reference loading over full-file reads
2. At high context pressure (>80%): truncate reference excerpts to essential sections only
3. At critical context pressure (>90%): skip remaining low-priority reference loading
4. MUST NOT sacrifice constraint resolution for token savings

---

Error Handling

Resource: Read resources/error-playbook.md on error occurrence.

Error Categories

Category	Example	Response
Agent timeout/failure	Agent Task does not return within 60s	Fallback to general guidance from orchestrator
Constraint conflict	Two agents impose contradictory requirements	Escalate to synthesizer with both positions
Missing reference data	Referenced document or section not found	Degrade gracefully; note data gap in output
Unknown domain	Query does not match any routing keywords	Return routing suggestions with related domains
Token budget exceeded	Cumulative tokens exceed budget guideline	Truncate reference excerpts; preserve agent analysis
Cross-system failure	One orchestrator fails in cross-system query	Return partial results from successful orchestrators with warning
Classification ambiguity	confidence < 0.50 after LLM classification	Ask user for domain clarification

Escalation Protocol

1. Agent fails       → Orchestrator provides fallback analysis
2. Orchestrator fails → Gateway Router provides high-level guidance
3. Multiple failures  → Report partial results + clear error summary to user
4. Total failure      → Return classification result + suggest manual domain selection

---

Context Health Protocol

Long sessions with multiple queries accumulate context. Monitor and manage proactively.

Thresholds

Usage	Level	Response
70%	WARNING	Minimize reference loading; rely on agent expertise
80%	RECOMMEND	Complete current query, then suggest /compact
85%	CRITICAL	Truncate all non-essential context; complete with minimal references

Recovery After /compact

1. /compact executed → context summarized
2. Check for classification result in context
3. IF not found AND mid-query:
   - Re-run classify-query.sh (fast, deterministic)
   - Re-read only the orchestrator .md needed for current phase
4. Resume from current phase

---

Status Display Protocol

Display current state at each phase entry.

Format

[engineering-workflow] Phase: {phase} | Pattern: {pattern} | Systems: {systems} | Budget: {used}/{total}K

Examples

[engineering-workflow] Phase: Classification | Pattern: pending | Systems: pending
[engineering-workflow] Phase: Agent Execution | Pattern: cross-system | Systems: DB,BE,SE | Budget: 5.8/14K

Session pattern caching: ~/.claude/cache/engineering-workflow/ (details in constraint-propagation.md)

---

Agents

Orchestrators (Tier 2)

Agent	Purpose	Model
db-orchestrator	Database system orchestration	sonnet
be-orchestrator	Backend system orchestration	sonnet
if-orchestrator	Infrastructure system orchestration (stub)	haiku
se-orchestrator	Security system orchestration	sonnet
synthesizer	Cross-system synthesis and constraint resolution	sonnet
audit-reviewer	Analysis quality audit (THOROUGH tier only)	sonnet

Micro Agents (Tier 3)

• DB: 6 domains (A-F), 18 agents — see db-orchestrator.md § Agent Selection Matrix
• BE: 4 clusters (S/B/R/T), 18 agents — see be-orchestrator.md § Agent Selection Matrix
• SE: 6 clusters (A/Z/E/N/C/V), 24 agents — see se-orchestrator.md § Agent Selection Matrix

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Resources (On-demand)

Document	Purpose
routing-protocol.md	Query classification algorithm and domain detection matrix
orchestration-protocol.md	Agent invocation procedure and Task prompt construction
constraint-propagation.md	Constraint flow, merge logic, and conflict resolution
be-orchestration-protocol.md	BE 4-cluster agent selection, chain rules, and dispatch protocol
error-playbook.md	Error handling procedures and fallback strategies
analysis-audit-protocol.md	Analysis Quality Gate, Contract Enforcement, Synthesis Validation
db-orchestration-protocol.md	DB agent selection matrix, dispatch protocol, and result merge algorithm
se-orchestration-protocol.md	SE 6-cluster agent selection, 8 chain rules, and security dispatch protocol
priority-matrix.md	Universal priority hierarchy for conflict resolution across all systems
synthesis-protocol.md	Cross-system synthesis procedure and dependency graph construction
confidence-calibration.md	5-factor confidence scoring rubric for micro agents
constraints-archetypes.json	Archetype library — preset constraint sets for common architecture patterns

Scripts

Script	Purpose
classify-query.sh	Deterministic keyword-based query classification (fast-path)
resolve-constraints.sh	Constraint conflict detection and auto-resolution
validate-agent-output.sh	Agent output JSON schema + quality indicator validation
audit-analysis.sh	Deterministic audit checks (confidence, schema, synthesis, tier)
format-output.sh	Output formatting for display (supports --summary for compact output, --graph for Mermaid constraint graph)
enforce-budget.sh	Token budget enforcement — exits non-zero if output exceeds 120% of budget
_common.sh	Shared utilities — imported by all other scripts (not called directly)

References (Static)

• DB: references/db/ — 18 files covering domains A-F (mapped in db-orchestrator.md § Load Reference Excerpts)
• BE: references/be/ — 11 files covering clusters S/B/R/T (mapped in be-orchestrator.md § Load Reference Excerpts)
• SE: references/se/ — 7 files covering clusters A/Z/E/N/C/V + best practices (mapped in se-orchestrator.md § Load Reference Excerpts)