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anamnesis_create_memory

Store concise memories from sources or chats to preserve decisions, patterns, and solutions. Add summary, tags, and project; include source_id to mark the source chunk processed.

Instructions

Store a new memory that you have crafted from reading a source or from the current conversation. The summary should be 2-3 focused sentences emphasizing keywords for future recollection. Include relevant technology names, pattern types, and problem descriptions. If source_id is provided, the source chunk will be marked as processed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outcomeNosolved
projectYes
summaryYes
source_idNo
artifact_ptrNo
context_tagsYes
project_pathNo
artifact_typeNonote

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It usefully discloses a side effect: providing source_id marks the source chunk as processed. However it says nothing about permissions, whether existing memories are overwritten, deduplication, or mutation scope for the remaining parameters.

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?

Four sentences, front-loaded with the core action and the format requirement. Mostly every sentence earns its place, though the keyword/technology-name guidance is somewhat list-like and could be tightened.

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

Completeness2/5

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

For an 8-parameter mutation tool with 0% schema coverage and no annotations, the description is thin: it explains summary content and one side effect but leaves most parameters and the overall mutation model unexplained. An output schema exists, so return values need not be covered, but the input contract is largely unaddressed.

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

Parameters2/5

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

Schema description coverage is 0% across 8 parameters, so the description must compensate, but it only addresses summary (format guidance) and source_id (processed-marking side effect). The six other parameters (outcome, project, artifact_ptr, context_tags, project_path, artifact_type) get no explanation at all.

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+resource ("Store a new memory") and clarifies the two sources it can come from (reading a source or the current conversation). An agent can distinguish it from the read-oriented siblings (recall, search, fetch_source), though it doesn't name them explicitly.

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?

Implies usage context (after crafting a memory from a source or conversation), which frames when to call it, but never states when NOT to use it or how it differs from sibling write paths like split_source. The condition for providing source_id is given, which is helpful, but overall usage guidance is only implied.

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