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memory_ingest

Convert ephemeral insights into permanent long-term memory; automatically chunks text, generates embeddings, and stores for semantic recall.

Instructions

Promote content into permanent long-term memory (demo.marsvault_chunks). Automatically chunks the input text, generates vector embeddings, and stores each segment for semantic recall. Use this to preserve important insights, decisions, patterns, or knowledge that should survive beyond the current session. This is the primary path from ephemeral to permanent memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe insight content to promote to long-term memory. Be specific and self-contained — future recall depends on the quality of this text.
source_fileNoLogical file path or identifier for the source (e.g. "sessions/2026-06-10-session-notes")
sectionNoOptional section label prefix to organize chunks within the source
tagsNoCategorization tags (e.g. ["decision", "architecture"])
typeNoContent type label (e.g. "insight", "observation", "decision")insight
dateNoDate for this content in YYYY-MM-DD format. Defaults to today if omitted.
visibilityNoAccess level: "private" = this profile only, "shared" = cross-profile readable, "global" = system-wideprivate
originNoOrigin markerwarp-demo
source_memory_idNoLink this promotion to a specific short-term memory ID (for traceability)
source_session_idNoSession ID where this insight originated (for provenance tracking)
source_toolNoThe tool/platform where this insight was originally captured
source_user_noteNoBrief note explaining why this memory was selected for promotion
agent_bodyNoThe persona/body this memory belongs to (e.g. "coco", "toto")
environmentNoEnvironment label (e.g. "production", "staging")
max_chunk_charsNoMaximum characters per chunk (default 1200). Adjust for finer or coarser granularity.
Behavior3/5

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

With no annotations, the description carries full burden. It discloses automatic chunking, vector embedding, and storage for semantic recall. Missing details on idempotency, side effects, or permissions. Adequate but not comprehensive.

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?

Two sentences, concise and front-loaded. The first sentence captures the core action; the second adds usage context. No wasted words, though could be slightly more structured.

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

Completeness3/5

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

Explains the promotion process and use case effectively. Missing details on return values (no output schema), error handling, or prerequisites. Adequate for a moderately complex tool.

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 covers all 15 parameters with descriptions. The description adds general context about chunking but no extra per-parameter value. Baseline 3 due to high schema coverage.

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's purpose: 'Promote content into permanent long-term memory' with specific actions like chunking and embedding. It distinguishes from siblings by calling it 'the primary path from ephemeral to permanent memory'.

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?

Provides clear guidance on when to use: 'preserve important insights, decisions, patterns, or knowledge that should survive beyond the current session.' However, it does not explicitly mention when not to use or contrast with siblings like batch_promote or dream_ingest.

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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