Workflow Modes
Snipara offers two workflow modes optimized for different task complexities. Choose LITE for quick fixes, FULL for complex features.
Token Savings: LITE mode uses ~3-5K tokens. FULL mode uses ~8-15K tokens but provides session continuity and memory.
Quick Decision
Ask yourself these 4 questions:
| Question | If Yes |
|---|---|
| Will this take multiple sessions? | +1 toward FULL |
| Does it affect 5+ files? | +1 toward FULL |
| Am I making architectural decisions? | +1 toward FULL |
| Will others need to understand this later? | +1 toward FULL |
Score 0-1 = LITE mode | Score 2+ = FULL mode
LITE Mode (Default)
Use for bug fixes, small features, single-session work, and tasks where you know exactly which files to modify.
LITE MODE WORKFLOW
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1. rlm_context_query("your task") # Get relevant context
2. Read specific files # Direct file access
3. Make changes # Edit code
4. Run tests locally # pnpm test / pytest
Token budget: ~3-5K from SniparaLITE Mode Example
rlm_context_query(query="fix null check authentication")# Read the specific file# Edit to add null checkpnpm testFULL Mode (Complex Features)
Use for multi-day features, architectural changes, team coordination, and documentation-heavy work that spans multiple sessions.
FULL MODE WORKFLOW
──────────────────
PHASE 1: CONTEXT GATHERING
├── rlm_shared_context() # Team standards
├── rlm_recall("feature area") # Past decisions
└── rlm_context_query(max_tokens=8000)# Deep context
PHASE 2: PLANNING
├── rlm_plan("feature description") # Execution plan
├── rlm_decompose("feature") # Break into tasks
└── rlm_remember(type="decision") # Store key choices
PHASE 3: DOCUMENTATION (if needed)
├── Create spec locally
├── rlm_upload_document() # Store for queries
└── rlm_store_summary() # Pre-compute
PHASE 4: IMPLEMENTATION (per sub-task)
├── rlm_inject("current context") # Session context
├── rlm_multi_query([...]) # Batch queries
├── execute_python(code) # Test logic
└── Edit files locally # Actual changes
PHASE 5: PERSIST (end of session)
├── rlm_remember(type="learning") # Store gotchas
└── rlm_remember(type="context") # Where you left off
Token budget: ~8-15K from SniparaFULL Mode Example
# Phase 1: Contextrlm_shared_context(categories=["BEST_PRACTICES"])rlm_recall(query="rate limiting decisions")rlm_context_query(query="API middleware", max_tokens=8000)# Phase 2: Planrlm_plan(query="implement rate limiting for API")rlm_remember(type="decision", content="Using Redis sliding window")# Phase 4: Implementrlm_inject(context="Working on rate limiting, Redis backend")rlm_multi_query(queries=[{query: "Redis patterns"}, ...])# Phase 5: End sessionrlm_remember(type="context", content="Completed middleware, next: tests")Mode Selection Examples
| Task | Mode | Why |
|---|---|---|
| Fix typo in README | LITE | Single file, obvious change |
| Fix null check in auth.ts | LITE | Known file, small fix |
| Add loading spinner | LITE | Single component |
| Add rate limiting to API | FULL | Multi-file, architectural |
| Refactor auth to JWT | FULL | Breaking change, multi-file |
| New billing integration | FULL | New feature, external API |
| Multi-tenant support | FULL | Architectural, multi-session |
Session Continuity (FULL Mode)
FULL mode enables work that spans multiple sessions through the memory system.
Starting a New Session
rlm_recall(query="feature-name progress status")rlm_context_query(query="feature-name")Ending a Session
rlm_remember(
type="context",
content="Feature X: Completed steps 1-3. Next: implement Y. Blocker: Z"
)Tools Reference
| Need | Tool | Mode |
|---|---|---|
| Quick answer | rlm_ask | Both |
| Deep context | rlm_context_query | Both |
| Past decisions | rlm_recall | FULL |
| Team standards | rlm_shared_context | FULL |
| Plan complex work | rlm_plan | FULL |
| Break down task | rlm_decompose | FULL |
| Save decision | rlm_remember | FULL |
| Batch queries | rlm_multi_query | FULL |
| Test logic | execute_python | FULL |