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memory_save

Save insights, patterns, or debugging solutions with semantic embedding for later retrieval. Automatically summarizes verbose content to preserve key information.

Instructions

Save a memory with semantic embedding. Use after learning something valuable.

Args:
    content: Memory content. Format: '[CATEGORY] - [insight]. Context: [where]. Rationale: [why]'
    category: One of PATTERN, CONFIG, DEBUG, PERF, PREF, INSIGHT, API, AGENT
    tags: Optional tags for categorization (auto-extracted if summarize=True)
    summarize: Use LLM to intelligently summarize verbose content

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
categoryNoINSIGHT
tagsNo
summarizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Adds behavioral details beyond annotations: semantic embedding, auto-tag extraction with summarize. Does not contradict annotations.

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?

Concise description with well-structured args list. Each sentence adds value, though could be more streamlined.

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 usage, parameters, and key behavior. Output schema exists, so return values not needed. Adequate for the tool's complexity.

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?

With 0% schema coverage, description adds meaningful formatting guidance for content, lists category options, and explains tags/summarize behavior.

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?

Clearly states verb 'save' and resource 'memory', with specific context 'with semantic embedding'. Distinguishes from sibling tools like memory_delete and memory_recall.

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?

Provides basic usage guidance ('Use after learning something valuable'), but lacks explicit when-not-to-use or comparisons to alternatives like memory_update.

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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