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CPersona

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archive_episode

Archive a conversation episode using pre-computed summary, keywords, and resolved status, storing it in CPersona for later recall.

Instructions

Archive a conversation episode with pre-computed summary, keywords, and resolved status. All LLM processing is performed by the caller. A summary that runs past the embedding window adds nodes:{status:'queued'} to the response, as on store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelNov2.4.22 conversation-channel tag (e.g. a Discord channel id). Default '' (= unscoped). Channel-scoped recall returns episodes whose channel matches; this powers the per-channel episodic loop.
historyNoOriginal conversation messages (used for start/end timestamp extraction; the episode embedding is computed from summary)
summaryYesEpisode summary (pre-computed by caller)
agent_idYesAgent identifier
keywordsNoSpace-separated keywords (pre-computed by caller)
resolvedNoWhether the topic was completed/concluded
project_idNov2.4.17 isolation axis. Omit or pass '' for the global pool. 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.
session_keyNoOpaque session identity you declare: a partition hint, not authentication and not a data filter. Selects which no-persist pause applies to this call. Omit to share one bucket with every caller that omits it. Full text on recall.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.6.1
    • addedInput schema / properties / session_key / maxLength
      Added value: +256
  2. Changed1 schema field changedv2.5.10
    • addedInput schema / properties / session_key
      Added value: +{
+  "default": "",
+  "description": "Opaque session identity you declare: a partition hint, not authentication and not a data filter. Selects which no-persist pause applies to this call. Omit to share one bucket with every caller that omits it. Full text on recall.",
+  "type": "string"
+}
  3. Changed1 schema field changedv2.5.2
    • changedInput schema / properties / project_id / description
      Previous value: -"v2.4.17 isolation axis. Omit or pass '' for the global pool."New value: +"v2.4.17 isolation axis. Omit or pass '' for the global pool. 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."
  4. Changed1 schema field changedv2.5.1
    • changedInput schema / properties / history / description
      Previous value: -"Original conversation messages (used for timestamp extraction and embedding)"New value: +"Original conversation messages (used for start/end timestamp extraction; the episode embedding is computed from summary)"
  5. Changed2 schema fields changedv2.4.34
    • addedInput schema / properties / channel
      Added value: +{
+  "description": "v2.4.22 conversation-channel tag (e.g. a Discord channel id). Default '' (= unscoped). Channel-scoped recall returns episodes whose channel matches; this powers the per-channel episodic loop.",
+  "type": "string"
+}
    • addedInput schema / properties / project_id
      Added value: +{
+  "description": "v2.4.17 isolation axis. Omit or pass '' for the global pool.",
+  "type": "string"
+}
  6. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false). The description adds genuine value beyond that: it discloses the caller-side LLM contract and the specific overflow behavior (nodes:{status:'queued'} when the summary exceeds the embedding window). It stops short of describing persistence semantics or auth requirements.

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

Conciseness5/5

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

Two tight sentences with no waste; the core purpose is front-loaded and the caller-processing constraint and queue behavior follow immediately. Nothing is redundant.

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?

There is no output schema, so the description usefully covers the one notable return-value shape (the queued node) and the caller-processing contract. For an 8-parameter mutation tool this is largely sufficient, though it could say more about persistence/dedup behavior.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 8 parameters in detail — including the complex project_id '@auto' resolution semantics. The description adds the summary/embedding-window interaction but no syntax or meaning for the remaining parameters, so the baseline 3 is appropriate.

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?

States a specific verb (archive) and resource (conversation episode) plus the key inputs (summary, keywords, resolved status). It implicitly separates itself from the sibling `store` by saying the queued behavior is 'as on store', which signals this is the episode-specific archive path rather than the generic store.

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?

'All LLM processing is performed by the caller' does imply the usage contract (caller must pre-compute the summary/keywords), but it never states when to choose this over siblings like store, list_episodes, or delete_episode. Usage is implied rather than explicitly routed.

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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