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Cloto-dev

CPersona

Official
by Cloto-dev

recall_with_context

Read-only

Retrieve relevant memories and merge them with conversation history, automatically deduplicating and sorting chronologically to produce a unified context list.

Instructions

Recall memories and merge with external conversation context. Automatically deduplicates, sorts chronologically, and returns a unified list. Replaces separate recall + manual merge in the caller. Content is preview-tiered by default — see recall's full_content / get_contents (full_content shares recall's 200k-char response budget, bug-211). Every external_context entry's content filters the recall (the caller already holds that text), but only role=user / role=assistant entries are merged into messages. When entries of other roles are present the response carries context_filter_only={roles:[...]} — those entries filtered the recall without appearing in the output, whether or not they dropped a memory this time. gate_fallback=true (absent otherwise) is forwarded from the underlying recall: every candidate fell below the quality gate and the below-gate lexical matches were returned instead of an empty result — treat them as low-confidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoDisable time decay
limitNoPer-retriever search depth for the underlying recall, not a pure response cap — same semantics as recall's limit (CSC #716): lowering it shrinks the candidate pool itself, not just the rows returned. (Agent-facing cap; the library layer accepts up to the scan window for direct callers.)
queryYesSearch query
channelNoMemory channel filter
agent_idYesAgent ID
source_idNov2.4.20 per-user source filter — passed through to recall. Same semantics as in `recall`.
project_idNov2.4.17 γ filter — passed through to recall. Same semantics as in `recall`. v2.5.1: pass '@auto' to resolve this agent's default from the server's operating context (the resolution is echoed as resolved_project_id; an unmapped agent yields operating_context_warning). bug-186: resolution requires a configured operating context. With none — the default, and equally the outcome of a sidecar that fails to parse — the sentinel is NOT resolved: it is stored and filtered as the literal project_id '@auto', resolved_project_id echoes '@auto', and no warning is raised. Read resolved_project_id before relying on the resolution.
full_contentNov2.5.0 preview tier opt-out — same semantics as in `recall`.
external_contextNoConversation history entries [{role, name?, user_id?, content, timestamp?}, ...]
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint annotation, the description discloses automatic deduplication, chronological sorting, preview-tiering, external_context filtering and role-based merging, the context_filter_only response field, and gate_fallback low-confidence semantics. This is rich behavioral context that goes far beyond what annotations alone provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured, with the purpose front-loaded and subsequent sentences covering important behavioral details and edge cases. It is longer than a minimal description, but every sentence carries substantive information for a complex tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the absence of an output schema, the description explains key response signals (context_filter_only, gate_fallback), preview-tiering behavior, external_context role handling, and the relationship to recall's budget. This is sufficient for an agent to understand the tool's behavior and edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers all 9 parameters, so the baseline is 3, but the description adds meaningful semantics for external_context (every entry's content filters recall, only user/assistant entries merge into messages) and full_content (shares recall's 200k-char response budget). This adds value beyond the schema's field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Recall memories and merge with external conversation context' and explicitly says it 'Replaces separate recall + manual merge in the caller,' clearly distinguishing this tool from sibling tools like recall and merge_memories. The verb-resource pair is specific and the scope is immediately understandable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear usage context by stating that this tool replaces the separate recall + manual merge flow, and points to recall's full_content / get_contents for full-content needs. However, it does not explicitly state when to prefer plain recall over this tool or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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