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Cloto-dev

CPersona

Official
by Cloto-dev

recall

Read-only

Retrieve relevant memories using hybrid search (vector, FTS5, keyword) with confidence scoring and match reasons. Preview content returned by default; expand with get_contents.

Instructions

Recall relevant memories using multi-strategy search (vector + FTS5 + keyword). Message content is returned as a preview tier by default — expand selected rows with get_contents(refs), or opt out wholesale with full_content=true. v2.5.2 additive: each scored message carries match_reason={signal, score, ...} where signal is the branch the ranking / quality gate keyed on (confidence > rsf > cosine > rrf) and the remaining keys (cosine / rrf / rsf) surface the internal per-retriever contributions present on that row. Unscored rows (cascade FTS/keyword) omit match_reason. A response carrying gate_fallback=true (absent otherwise) means 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
deepNoDeep recall — disable time and completion decay for exhaustive search
limitNoMax memories to return (agent-facing cap; the library layer accepts up to the scan window for direct callers)
queryYesSearch query (empty returns recent memories)
channelNoFilter memories by channel (e.g. 'chat', 'discord'). Default: '' (all channels).
agent_idYesAgent identifier
source_idNov2.4.20 per-user source filter. Empty (default) = no filter. Non-empty = prefix match against json_extract(source, '$.id'), e.g. 'discord:12345' to restrict to one Discord user, or 'discord:' to scope to all Discord-sourced memories. Episodes carry no per-user source tagging, so they are skipped when this is set — UNLESS channel is also set, which scopes episodes to one conversation and re-admits them.
project_idNov2.4.17 γ filter. Omit → no filter (all projects). '' → global pool only. 'X' → 'X' bucket ∪ global pool. Threaded through cascade / RRF / vector / FTS / keyword paths. 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. By default message content longer than the preview cap (CPERSONA_RECALL_PREVIEW_CHARS, default 500) is returned as a pure prefix with content_truncated/content_len markers; each message's `ref` expands via get_contents. true returns full text.
exclude_contentsNoNormalized content strings to exclude from results (starts-with match). Used to prevent duplication with conversation context already known to the caller.
Behavior5/5

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

The description goes far beyond the readOnlyHint annotation, disclosing numerous behavioral traits: preview tier behavior, match_reason structure (including signal and per-retriever contributions), gate_fallback mechanism, and project_id resolution nuances (including bug-186). No contradictions with annotations; very transparent.

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

Conciseness3/5

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

The description is comprehensive but verbose, especially with version-specific details and bug references. It covers many details, which aids completeness but reduces conciseness. Front-loading is present (starts with purpose), but the length may overwhelm agent parsing.

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 (9 parameters, no output schema), the description is remarkably complete. It explains match_reason for scored rows, gate_fallback for low-confidence results, project_id resolution quirks, source_id filtering behavior, and the interplay with channels. No gaps identified for an agent to use the tool effectively.

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

Parameters5/5

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

While schema coverage is 100%, the description adds substantial meaning: version details (v2.5.0, v2.5.1, bug-186), default behaviors, edge cases (gate_fallback, source_id prefix matching, project_id resolution with '@auto'), and inter-parameter dependencies (channel re-admits episodes). This is far beyond the schema descriptions.

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

Purpose4/5

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

The description clearly states the tool recalls relevant memories using multi-strategy search (vector + FTS5 + keyword). It mentions the return format and preview tier, which helps understand the purpose. However, it does not explicitly differentiate from sibling tools like 'recall_with_context' or 'list_memories', which could lead to confusion about when to use which tool.

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

Usage Guidelines3/5

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

The description provides detailed parameter guidance (e.g., when to use full_content, source_id, project_id), but lacks explicit direction on when to use this tool versus alternatives like 'recall_with_context' or 'get_contents'. Usage context is implied rather than stated, leaving some ambiguity for the agent.

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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