Skip to main content
Glama
Cloto-dev

CPersona

Official
by Cloto-dev

recall_with_context

Read-only

Merge recalled memories with external conversation context, deduplicating and sorting chronologically to produce a unified 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. 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
limitNoMax recalled memories (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?

Annotations only provide readOnlyHint: true, while the description details deduplication, chronological sorting, preview-tiering, special handling of external_context roles, and gate_fallback behavior. No contradiction with annotations.

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 a single dense paragraph that conveys a lot of information. While not excessively long, it could benefit from more structured formatting (e.g., bullet points). It is mostly concise but slightly run-on.

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

Completeness4/5

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

No output schema exists, so the description must cover return behavior. It explains the unified list, context_filter_only, and gate_fallback, but does not fully describe the output structure. Overall, it provides substantial context for a complex tool.

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?

Schema coverage is 100%, so the descriptions already cover each parameter. The tool description adds extra meaning by explaining how external_context entries affect filtering and merging, going beyond the schema.

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 clearly states the tool recalls memories and merges with external context, automatically deduplicating and sorting chronologically. It explicitly distinguishes itself from sibling tools like 'recall' by noting it 'replaces separate recall + manual merge in the caller.'

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?

The description explains when to use this tool over manual merging and mentions preview-tiering with references to 'recall's full_content / get_contents'. However, it does not explicitly state when not to use it or provide exclusion criteria.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Cloto-dev/CPersona'

If you have feedback or need assistance with the MCP directory API, please join our Discord server