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xultrax-web

agent-memory-mcp

by xultrax-web

save_memory

Save or update structured memories as markdown files with YAML frontmatter, categorized by type (user, feedback, project, reference, rule) and optional tags for search ranking.

Instructions

Save (or update) a memory. Memories are markdown files with YAML frontmatter, stored at the resolved memory dir. Use a short kebab-case name; the description is what's shown in the index and used for search ranking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesShort kebab-case slug, 1-80 chars (e.g. 'user-prefers-tabs')
tagsNoOptional tags for cross-cutting categorization. Lowercase, kebab/underscore, max 40 chars each. Queryable in list_memories + search_memories.
typeYesMemory type: user (about the person), feedback (lessons + corrections), project (state/context), reference (external pointers), rule (constraint enforced via companion files — prefer the save_rule tool which validates rule-specific fields)
contentYesMarkdown body. For feedback/project, include **Why:** and **How to apply:** lines.
descriptionYesOne-line summary, shown in the index and ranked highly in search
Behavior3/5

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

The description explains that memories are markdown files with YAML frontmatter and gives naming conventions. It implies idempotency by stating 'Save (or update)'. Without annotations, the description carries some burden, but it omits details like permissions, rate limits, or side effects.

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

Conciseness5/5

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

Two sentences, no fluff. First sentence states the tool's action and file format, second gives key naming/index guidance. Information is front-loaded and efficient.

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?

Given the 5 parameters, no annotations, and no output schema, the description covers the core behavior but lacks details on idempotency, error handling, or return value. The schema is well-documented but the description could be more complete.

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 description coverage is 100%, so baseline is 3. The description adds value by explaining that the 'name' should be kebab-case and the 'description' is used for indexing and search ranking, which is not in the 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 (or update) a memory' and explains what memories are. However, it does not explicitly differentiate from the sibling tool 'save_rule', though the schema includes that hint. The purpose is specific and actionable.

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?

The description provides no guidance on when to use this tool versus alternatives like save_rule. The usage hint for rule types is only in the parameter schema, not in the main description, so the agent lacks direct guidance.

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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