memora

memory_insights

Analyze stored memories to produce actionable insights: activity summaries, open items, and consolidation candidates. Optionally detect patterns and gaps with LLM analysis.

Instructions

Analyze stored memories and produce actionable insights.

Returns activity summary, open items, consolidation suggestions, and optional LLM-powered pattern detection.

Args: period: Time period to analyze (e.g., "7d", "1m", "1y") include_llm_analysis: If True, use LLM to detect patterns and themes

Returns: Dictionary with: - activity_summary: Created counts by type and tag - open_items: Open TODOs and issues with stale detection - consolidation_candidates: Similar memory pairs that could be merged - llm_analysis: Themes, focus areas, gaps, and summary (or null) Rate limited: 120s cooldown.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`period`	No		7d
`include_llm_analysis`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 2, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Mentions rate limiting (120s cooldown), which is helpful. Implies read-only operation via 'analyze' and 'returns' but does not explicitly state it does not modify data. Lacks details on potential costs or time for LLM analysis.

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

Conciseness3/5

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

Structured with Args and Returns sections, but includes some redundancy and could be more concise. The rate limit info is placed at the end, somewhat separate from the main description.

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?

Covers parameters, return values, and rate limit. Has output schema available in context, so description's detail on returns is appropriate. Lacks prerequisites or error conditions but is generally sufficient for its scope.

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 0%, so description compensates well. Provides example values for 'period' and explains effect of 'include_llm_analysis'. Adds meaning beyond the bare 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?

Clearly states the tool analyzes memories and produces actionable insights, listing returns like activity summary, open items, etc. However, it does not differentiate from similar analysis tools like memory_stats or memory_clusters, so some ambiguity remains among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description explains what it does but does not mention scenarios or conditions for use, nor when to avoid it.

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

Deploy Server