By name: rlm-workflow description: MUST use WHEN you are writing reusable knowledge into RLM (pattern / architectural decision / stable domain fact) OR reading it before a non-trivial task/solution in the domain. Provides the breakdown of native-push vs RLM-pull, tools for writing and reading RLM, H-MEM levels, and hygiene. alwaysApply: false
RLM Workflow — writing and reading knowledge
RLM is a pull storage for universal reusable knowledge: patterns, architectural decisions, domain facts for 1С/БСП, module findings. It is retrieved by topic through semantic search (embeddings fine-tuned for 1С) and does NOT stay in the context. The triggers for "when to write / when to read" are in the
rlm-workflowrule; here is how to do it.
Memory layout
| Knowledge | Layer | Tool |
|---|---|---|
| Always-on core (security, invariants, standing preferences) | native push | MEMORY.md + memory/*.md |
| Universal reusable knowledge (patterns, solutions, domain facts) | RLM pull | this skill |
| Transient task state (PENDING, next step, WIP) | agent-context | task_dir/.context/*.md |
Writing to RLM
Precondition (MUST): rlm_start_session() before any writes — otherwise silent failure (you only learn about it through rlm_get_hierarchy_stats).
| What to write | Call |
|---|---|
| Universal pattern / anti-pattern | rlm_add_hierarchical_fact(content, level=1, domain="retrospective") |
| Detail of a specific module/file | rlm_add_hierarchical_fact(content, level=2, domain="<domain>", module="<path>", code_ref="<file:line>") |
| Temporary note / hypothesis | rlm_add_hierarchical_fact(content, level=3, ttl_days=7) — auto-consolidation |
| Decision with alternatives | rlm_record_causal_decision(decision, reasons, consequences, constraints, alternatives) |
Finalizing the write — rlm_sync_state().
H-MEM levels:
level |
Name | When |
|---|---|---|
0 |
L0_PROJECT |
Loaded always. Critical global knowledge, project pitfalls. Write rarely (bloats every start) |
1 |
L1_DOMAIN |
By context. Stable patterns, session decisions |
2 |
L2_MODULE |
On request. Implementation details, findings at the module level |
3 |
L3_CODE |
Temporary. Auto-collapses into L2/L1 via rlm_consolidate_facts |
Reading from RLM
At the boundary of work (entering a non-trivial task / before an architectural decision / when a recurring problem appears) — one call, not a tool sweep:
| Goal | Call |
|---|---|
| Topic context (recommended, one-call) | rlm_enterprise_context(query="<domain/symptom>", max_tokens=3000) — auto-routing of L0 + relevant L1/L2 + causal chains |
| Only relevant facts within budget | rlm_route_context(query, max_tokens=2000) — L0 always + L1/L2 by similarity |
| Targeted hybrid search | rlm_search_facts(query, semantic_weight, keyword_weight, recency_weight, top_k) |
Weights in rlm_search_facts: semantic query → raise semantic_weight; search by exact term/identifier → raise keyword_weight; "what was changed recently" → recency_weight.
Hygiene
rlm_get_stale_facts()→ if neededrlm_delete_fact().- ≥5 granular facts on one topic →
rlm_consolidate_facts(min_facts=5)(L3→L2→L1 + dedup). - TTL: L3 → 7..14 days; L2 → 30..90; L1/L0 — no TTL.
- The first work with a project —
rlm_discover_project(project_root, task_hint)once (seeds the L0 structure).
Anti-patterns
| Anti-pattern | Consequence |
|---|---|
Writing without rlm_start_session |
Silent failure |
| Writing everything into L0 "just in case" | L0 is loaded always → every start becomes more expensive |
| Keeping universal knowledge in the native always-on core | Bloats context on every turn — this belongs in RLM (pull) |
| Putting transient (PENDING, WIP) into RLM | Pollutes the knowledge store; transient → agent-context |
| Reading RLM on every turn | Pull degrades into push; read at the boundary of work |