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labyrinth-analytics

LoreConvo

Official

Save Session

save_session

Save session summaries, decisions, and artifacts to persistent memory for recall in future sessions. Ensures context continuity across AI agent interactions.

Instructions

Save a session summary to persistent memory.

Call this at the end of a session or when the user requests /bridge save. Captures decisions, artifacts, skills used, and open questions for recall in future sessions.

Args: title: Short descriptive title for the session surface: Where this session ran - 'cowork', 'code', or 'chat' summary: 2-3 paragraph narrative summary of what happened decisions: List of key decisions made during the session artifacts: List of files created or modified open_questions: Unresolved questions to carry forward tags: Freeform tags for categorization skills_used: Skills that were invoked during this session project: Project name if part of a defined project start_date: ISO 8601 start time (defaults to now) end_date: ISO 8601 end time session_id: Optional session ID to enable deduplication with the auto-save hook. If a session with this ID already exists (e.g., auto-saved at session end), the record is updated with the richer manual metadata. Artifacts from the existing record are preserved when the caller does not supply artifacts. If omitted, a new UUID is generated (existing behavior). external_tool_session: Set True when saving a session generated by an external tool (e.g., Anthropic Managed Agents). Flagged sessions are excluded from auto-load and search by default to prevent context contamination. Override exclusion with include_external=True on search, or set LORECONVO_EXTERNAL_TOOL_EXCLUSION=0 to disable globally. reasoning_notes: Optional free-form text capturing the reasoning chain or thought process behind decisions. Stored as-is; blank or None leaves the field empty. summarize: If True and ANTHROPIC_API_KEY is set, send the summary to Claude API (Haiku) for compression before saving. Opt-in only; defaults to False. Falls back to the raw summary on any API error or if the key is absent. See INSTALL.md Privacy Note.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
titleYes
projectNo
summaryYes
surfaceYes
end_dateNo
artifactsNo
decisionsNo
summarizeNo
session_idNo
start_dateNo
skills_usedNo
open_questionsNo
reasoning_notesNo
external_tool_sessionNo
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: persistent memory storage, deduplication via session_id, update behavior preserving artifacts, exclusion of external tool sessions from auto-load/search, and opt-in summarization via Claude API. All key behavioral aspects are covered.

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 fairly long but well-structured with a brief intro, usage trigger, and detailed parameter list. Each sentence adds value; minor redundancy could be trimmed (e.g., the session_id explanation is somewhat verbose), but overall efficient.

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 15 parameters, 3 required, no output schema, the description covers all parameters and behavioral nuances including deduplication, update semantics, exclusion logic, and summarization. It is complete for a save operation with no gaps.

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?

Schema has 0% description coverage, so the parameter descriptions carry full burden. Each of the 15 parameters is explained with purpose, defaults, and behavioral nuance (e.g., session_id deduplication, external_tool_session exclusion, summarize opt-in). This significantly adds meaning beyond the raw schema.

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 'Save a session summary to persistent memory' with a specific verb and resource. It mentions when to call (end of session or /bridge save), but does not explicitly differentiate from sibling tools like consolidate_memories or import_sessions, though the purpose is distinct.

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 provides explicit usage context: 'Call this at the end of a session or when the user requests /bridge save.' It does not specify when not to use or mention alternatives, but the trigger is clear and sufficient for most scenarios.

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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