memory-router

name	memory-router
description	Central dispatch layer for OpenClaw Memory Stack. Routes memory queries to the best backend via signal detection, class-based dispatch, and sequential fallback.
license	MIT
metadata	{"authors":"OpenClaw Memory Stack","version":"0.1.0"}

Memory Router — SKILL.md

Overview

Memory Router is the central dispatch layer of the OpenClaw Memory Stack. It receives memory queries from the AI agent and routes them to the appropriate backend based on a deterministic rule table with sequential fallback. It is not an AI-powered optimizer — it is a rule-based router with explicit signal matching and a well-defined fallback chain.

How it works:

1. Read ~/.openclaw/state/backends.json to discover which backends are installed.
2. Match the incoming query against the routing rule table (top-to-bottom, first match wins).
3. Dispatch to the primary backend.
4. If the result is poor (normalized_relevance < 0.4, status = empty, or status = error), fall back sequentially through the fallback chain.
5. Return the best result found, wrapped in the router envelope.

The router adds zero storage — it is purely a dispatch and fallback coordinator. All actual memory operations happen in the backends.

Prerequisites

• ~/.openclaw/state/backends.json must exist and list installed backends.
• At least one backend must be installed (QMD and Total Recall are always present in Starter).
• The router itself has no runtime dependencies beyond the ability to read JSON and invoke backend skills.

Routing Rules

Tier-Aware Backend Discovery

Before evaluating rules, the router reads ~/.openclaw/state/backends.json to build the candidate list of available backends. If a backend appears in a routing rule but is not in the candidate list, it is silently skipped — no error, no warning. The fallback chain advances to the next available backend.

Starter tier (QMD + Total Recall): Cognee and Lossless rules are effectively disabled — queries that would route to them fall through to QMD or Total Recall alternatives automatically.

Pro tier (all 4 backends): The full routing table is active.

Rule Table

Rules are evaluated top-to-bottom. The first rule whose signal matches the query wins. If no rule matches, the default rule applies.

#	Signal in Query	Primary Backend	Fallback Chain	Rationale
1	Exact symbol, function name, class name, method name (find function, find class, find method, or a CamelCase/snake_case identifier)	QMD (search mode)	Total Recall	BM25 excels at exact token matching on code identifiers
2	Relationship query: "how does X relate to Y", "dependency between", "connection between", "what depends on", "call chain", "trace from...to"	Cognee	QMD (vsearch) > Total Recall	Graph traversal is required to follow entity relationships
3	Decision recall: "what did we decide about", "earlier in conversation", "decision from", "why did we choose", "recall the decision"	Lossless	Total Recall > QMD (search)	DAG preserves causal decision chains from conversation history
4	Concept/behavior query: "how does X work", "where is Y handled", "explain the...strategy", "what is the approach for"	QMD (vsearch mode)	QMD (query) > Total Recall	Vector semantic search finds conceptually related code
5	Recent context: "just discussed", "few minutes ago", "last change", "what was the last thing", "recently"	Total Recall	QMD (search)	Time-decay relevance prioritizes recent memories
6	File/path pattern: "in src/auth/", "*.swift files", file path segments, glob patterns	QMD (search mode)	Total Recall	BM25 path-based search matches filesystem patterns
7	Ambiguous / no clear signal (single words, vague references, catch-all)	QMD (query mode)	Total Recall	Hybrid search (BM25 + vector) is the safest default for unclear intent

Rule 7 is the default rule. If no signal from rules 1-6 is detected, the query routes to QMD hybrid search.

Signal Detection

Signal matching uses keyword and pattern detection, not semantic understanding. The router looks for:

• Rule 1 (exact symbol): Query contains find.*function, find.*class, find.*method, find all usages of, search for, or a token that matches CamelCase/snake_case identifier patterns.
• Rule 2 (relationship): Query contains relate, relationship, depends on, dependency, connection, call chain, trace.*to, path between.
• Rule 3 (decision recall): Query contains decide, decision, chose, why did we, recall.*decision, earlier in conversation, morning session, afternoon session.
• Rule 4 (concept/behavior): Query contains how does.*work, where is.*handled, explain, strategy, approach for, what is the.*for.
• Rule 5 (recent context): Query contains just discussed, few minutes ago, last change, recently, last thing, what was the last.
• Rule 6 (file/path): Query contains file path separators (/), glob patterns (*, **), or file extensions (.ts, .swift, .py, etc.).
• Rule 7 (default): No signal detected from rules 1-6.

Fallback Logic

The fallback mechanism is sequential and deterministic:

1. Dispatch to primary backend per the matched rule.
2. Evaluate the response:
   • normalized_relevance >= 0.4 AND status = success — Accept the result. Done.
   • normalized_relevance < 0.4 OR status = empty — Result is insufficient. Move to next backend in fallback chain.
   • status = error — Immediate fallback. Log the error to ~/.openclaw/state/router.log.
3. Timeout enforcement: The router measures wall-clock time for each backend call. If a backend exceeds 5000ms, the router marks the response as QUERY_TIMEOUT and moves to the next backend in the chain.
4. Chain exhaustion: If the entire fallback chain is exhausted without a good result (normalized_relevance >= 0.4), the router returns the best result found across all attempted backends (even if < 0.4) with status: partial.
5. Total failure: If every backend in the chain returns status = error, the router returns:

{
  "status": "error",
  "error_code": "ALL_BACKENDS_FAILED",
  "error_message": "All backends in the fallback chain failed. Check ~/.openclaw/state/router.log for details."
}

Fallback Behavior with Missing Backends

When a backend in the fallback chain is not installed (not in backends.json), the router skips it silently and advances to the next entry. This is how Starter tier works naturally — Cognee and Lossless are simply not in the candidate list, so rules 2 and 3 fall through to their QMD/Total Recall alternatives.

Example — Rule 2 on Starter tier:

• Primary: Cognee (not installed) — skip
• Fallback 1: QMD vsearch — execute
• Fallback 2: Total Recall — execute if QMD result is poor

Few-Shot Routing Examples

Clear Queries (10)

1. "find the function parseAuthToken"

• Signal: find.*function + CamelCase identifier
• Rule matched: #1 (exact symbol)
• Routed to: QMD search mode
• Fallback chain: [Total Recall]

2. "how does the auth middleware relate to the session store"

• Signal: relate keyword, two identifiable entities
• Rule matched: #2 (relationship)
• Routed to: Cognee (if Pro), else QMD vsearch (Starter fallthrough)
• Fallback chain: [QMD vsearch, Total Recall]

3. "what did we decide about the database schema in the morning session"

• Signal: decide keyword, morning session
• Rule matched: #3 (decision recall)
• Routed to: Lossless (if Pro), else Total Recall (Starter fallthrough)
• Fallback chain: [Total Recall, QMD search]

4. "how does error handling work in the API layer"

• Signal: how does.*work
• Rule matched: #4 (concept/behavior)
• Routed to: QMD vsearch
• Fallback chain: [QMD query, Total Recall]

5. "what was the last thing we changed"

• Signal: last thing
• Rule matched: #5 (recent context)
• Routed to: Total Recall
• Fallback chain: [QMD search]

6. "search in src/models/*.ts"

• Signal: file path separator /, glob pattern *, extension .ts
• Rule matched: #6 (file/path pattern)
• Routed to: QMD search
• Fallback chain: [Total Recall]

7. "find all usages of UserService"

• Signal: find all usages of + CamelCase identifier
• Rule matched: #1 (exact symbol)
• Routed to: QMD search
• Fallback chain: [Total Recall]

8. "what's the relationship between OrderController and PaymentService"

• Signal: relationship keyword, two CamelCase entities
• Rule matched: #2 (relationship)
• Routed to: Cognee (Pro) / QMD vsearch (Starter)
• Fallback chain: [QMD vsearch, Total Recall]

9. "recall the architecture decision from this morning"

• Signal: recall.*decision, morning
• Rule matched: #3 (decision recall)
• Routed to: Lossless (Pro) / Total Recall (Starter)
• Fallback chain: [Total Recall, QMD search]

10. "explain the caching strategy"

• Signal: explain, strategy
• Rule matched: #4 (concept/behavior)
• Routed to: QMD vsearch
• Fallback chain: [QMD query, Total Recall]

Ambiguous Queries (5)

11. "auth"

• Signal: Single word, no verb, no clear pattern.
• Rule matched: #7 (default — no signal detected)
• Routed to: QMD query (hybrid search)
• Fallback chain: [Total Recall]
• Rationale: Single words have no clear intent. Hybrid search (BM25 + vector) covers the most ground. Could be a symbol name, a concept, or a path fragment — QMD query handles all three reasonably.

12. "that thing with the tokens"

• Signal: Vague demonstrative "that thing" hints at recent context, but no explicit recency keyword.
• Rule matched: #5 (recent context — weak signal from "that thing")
• Routed to: Total Recall
• Fallback chain: [QMD query]
• Rationale: "that thing" is a conversational back-reference suggesting the user means something discussed recently. Total Recall's time-decay scoring gives the best chance. If nothing recent matches, QMD hybrid search broadens the scope.

13. "database"

• Signal: Single word, no verb, no clear pattern.
• Rule matched: #7 (default — no signal detected)
• Routed to: QMD query (hybrid search)
• Fallback chain: [Total Recall]
• Rationale: Could mean schema, configuration, relationship, migration, or connection string. Hybrid search is the safest bet for a single ambiguous term.

14. "why did we do it that way"

• Signal: why did we maps to decision recall.
• Rule matched: #3 (decision recall)
• Routed to: Lossless (Pro) / Total Recall (Starter)
• Fallback chain: [Total Recall, QMD search]
• Rationale: "why did we" is a strong decision-recall signal. The user wants the reasoning behind a past choice. Lossless DAG traces causal chains to reconstruct the decision rationale.

15. "the middleware issue"

• Signal: No verb, no clear pattern. "issue" is generic — could be a bug, a relationship, or recent context.
• Rule matched: #7 (default — no signal detected)
• Routed to: QMD query (hybrid search)
• Fallback chain: [Total Recall]
• Rationale: "the middleware issue" is too vague for any specialized backend. Hybrid search maximizes the chance of finding relevant content regardless of whether it was stored as a decision, a code change, or a concept note.

Output Format

The router wraps backend responses in a router envelope that adds routing metadata:

{
  "query_echo": "original query",
  "routed_to": "qmd",
  "routed_mode": "search",
  "fallback_chain": ["qmd", "totalrecall"],
  "fallbacks_used": 0,
  "results": [
    {
      "content": "matched content...",
      "relevance": 0.82,
      "source": "qmd",
      "timestamp": "2026-03-10T14:30:00Z"
    }
  ],
  "result_count": 2,
  "normalized_relevance": 0.82,
  "status": "success"
   
   

Router Envelope Fields

Field	Type	Description
query_echo	string	The original query string, unchanged
routed_to	string	Backend that produced the returned results (qmd, totalrecall, cognee, lossless)
routed_mode	string | null	Mode used for the winning backend (e.g., search, vsearch, query for QMD; null for other backends)
fallback_chain	string[]	The complete fallback chain that was planned for this query
fallbacks_used	int	Number of fallbacks that were actually triggered (0 = primary succeeded)
results	array	Standard result array from the winning backend (same structure as backend contract)
result_count	int	Number of results returned
normalized_relevance	float	The normalized relevance score from the winning backend (0.0-1.0). This is the value used for fallback decisions.
status	string	success, partial, empty, or error
router_duration_ms	int	Total wall-clock time for the entire routing operation (including all fallbacks)
backend_duration_ms	int	Duration of the winning backend call only

Status Values

Status	Meaning
success	Primary or fallback backend returned normalized_relevance >= 0.4
partial	Entire fallback chain exhausted; returning best result found (< 0.4)
empty	All backends returned no results
error	All backends failed (see error_code and error_message)

Error Handling

Backend Not Installed

If a backend appears in a routing rule but is not listed in ~/.openclaw/state/backends.json, the router skips it and advances to the next entry in the fallback chain. No error is logged — this is normal operation for Starter tier.

Backend Returns Error

Log the error to ~/.openclaw/state/router.log with timestamp, backend name, error code, and error message. Then advance to the next entry in the fallback chain.

Backend Timeout

If a backend call exceeds 5000ms (measured by the router), mark the response as QUERY_TIMEOUT, log it, and advance to the next entry in the fallback chain.

All Backends Fail

Return:

{
  "query_echo": "original query",
  "routed_to": null,
  "fallback_chain": ["qmd", "totalrecall"],
  "fallbacks_used": 2,
  "results": [],
  "result_count": 0,
  "status": "error",
  "error_code": "ALL_BACKENDS_FAILED",
  "error_message": "All backends in the fallback chain failed. Check ~/.openclaw/state/router.log for details.",
  "router_duration_ms": 10200,
  "backend_duration_ms": 0
}

Router Log Format

Each log entry in ~/.openclaw/state/router.log:

[2026-03-17T14:30:00Z] FALLBACK query="auth middleware" backend=cognee error_code=BACKEND_ERROR error_message="Python process exited with code 1" next=qmd
[2026-03-17T14:30:01Z] TIMEOUT query="auth middleware" backend=qmd duration_ms=5230 next=totalrecall

Configuration

The router reads two configuration sources:

1. ~/.openclaw/state/backends.json — Dynamic state file listing installed backends and their status.
2. router-config.json (alongside this file) — Static routing rules, thresholds, and tier configuration.

The router does not write to backends.json — that file is managed by the installer (setup.sh / install-pro.sh).

Limitations

• No learning or adaptation. The router uses static rules. It does not learn from past query patterns or adjust routing based on backend performance over time.
• Signal detection is keyword-based. The router cannot understand nuance. A query like "show me the auth flow" might match rule 4 (concept) when the user actually wanted rule 2 (relationship). The fallback chain mitigates this.
• No multi-backend merging. The router returns results from a single backend (the first one that meets the relevance threshold). It does not merge or deduplicate results across backends.
• Fallback adds latency. Each fallback attempt adds the backend's response time. In the worst case (all backends timeout), the router takes 3-4x the single-backend timeout.
• Rule order matters. Rules are evaluated top-to-bottom. If a query matches both rule 2 (relationship) and rule 4 (concept), rule 2 wins because it appears first. This is by design but may occasionally route to a suboptimal backend.

Tier

Starter — The router itself is always available. Its effectiveness scales with the number of installed backends: Starter tier routes to QMD and Total Recall; Pro tier unlocks Cognee and Lossless routing rules.