Cross-Agent Recall

An agent can recall memories from multiple banks in parallel. This lets one agent draw on knowledge from across the fleet -- a strategic advisor reading from the operations agent's bank, or a knowledge librarian pulling from every agent in the system.

How it works

When an agent with recallFrom configured receives a message, it sends the same recall query to all listed banks simultaneously. Results from each bank are interleaved using round-robin and injected into the prompt as a single combined context.

Configuration

Add recallFrom to the agent's bank config. Each entry specifies a bank ID and optional per-bank overrides:

// .openclaw/banks/yoda.json5
{
  "recallFrom": [
    { "bankId": "yoda" },
    { "bankId": "k2so", "budget": "low", "maxTokens": 512 },
    { "bankId": "c3po", "budget": "low", "maxTokens": 512 }
  ],
  "recallBudget": "high",
  "recallMaxTokens": 2048
}

Note that the agent's own bank should be included in the list if you want it to recall from itself. The recallFrom list replaces the default single-bank behavior -- it does not add to it.

Per-bank overrides

Each entry in recallFrom accepts:

Field	Type	Description
bankId	string	Target bank ID (required)
budget	low / mid / high	Override recall effort for this bank
maxTokens	number	Override max tokens for this bank
types	string[]	Override memory types (world, experience, observation)
tagGroups	TagGroup[]	Override tag filter for this bank

Fields not specified fall back to the agent's top-level recallBudget and recallMaxTokens.

Permission checks

When access control is active, permissions are checked independently for each target bank. The requesting user must have recall: true on each bank they read from.

If the current user has recall: false on bank c3po (resolved through the permission resolution algorithm), that bank is silently skipped. The agent still recalls from the remaining permitted banks.

This means cross-agent recall respects the same access control rules as single-bank recall. No unauthorized cross-reads.

Round-robin interleave

Results from multiple banks are merged using round-robin interleaving -- one result from each bank in turn, cycling until all results are exhausted. This prevents any single bank from dominating the context window.

Given three banks returning 4, 2, and 3 results respectively:

Bank A: [A1, A2, A3, A4]
Bank B: [B1, B2]
Bank C: [C1, C2, C3]

Interleaved: [A1, B1, C1, A2, B2, C2, A3, C3, A4]

The interleaved results are then formatted and injected into the prompt as a single <hindsight_memories> block.

Budget distribution

Each bank in recallFrom makes its own recall request with its own budget and token limit. The budgets are not split from a global pool -- each bank gets the full budget specified in its entry (or the agent-level default).

A practical pattern is to give the agent's own bank a higher budget and secondary banks a lower one:

{
  "recallFrom": [
    { "bankId": "yoda", "budget": "high", "maxTokens": 2048 },
    { "bankId": "k2so", "budget": "low", "maxTokens": 256 },
    { "bankId": "c3po", "budget": "low", "maxTokens": 256 }
  ]
}

This prioritizes the agent's own memories while still pulling relevant context from other banks.

In-flight deduplication

Concurrent recall requests for the same bank and query are deduplicated automatically. If two hooks trigger recall for the same bank with the same query text, only one HTTP request is made. This is transparent and requires no configuration.

Practical example

A CEO advisor agent (yoda) that draws from the operations agent (k2so) and the knowledge librarian (c3po):

// .openclaw/banks/yoda.json5
{
  "retain_mission": "Extract strategic decisions and cross-departmental patterns.",

  "recallFrom": [
    { "bankId": "yoda" },
    { "bankId": "k2so", "budget": "low", "maxTokens": 512 },
    { "bankId": "c3po", "budget": "low", "maxTokens": 512 }
  ],
  "recallBudget": "high",
  "recallMaxTokens": 2048
}

When alice asks yoda "What did we decide about the office expansion?", yoda sends the query to all three banks in parallel, checks alice's permissions on each, interleaves the results, and injects them into the prompt. The response draws on yoda's strategic context, k2so's operational details, and c3po's documented knowledge.