Penfield Memory

save_artifact

Save an artifact to storage.

Stores user-created content (diagrams, notes, code) in an organized
file structure. Content is also indexed for search.

Args:
    content: File content to save
    path: Full path including filename (e.g., "/project/docs/api.md")
    
Returns:
    Success message or error description
    
Examples:
    >>> await save_artifact("# README", "/readme.md")
    "✅ Artifact saved: /readme.md (8 bytes)"
    
    >>> await save_artifact("<svg>...</svg>", "/diagrams/architecture.svg")
    "✅ Artifact saved: /diagrams/architecture.svg (image/svg+xml, 45 bytes)"

Input Schema

TableJSON Schema

Name	Required	Description	Default
`path`	Yes
`content`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedMar 16, 2026

TDQS

A4.1/5.0

Behavior3/5

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

Annotations indicate it's not read-only (readOnlyHint=false), and description confirms it's a write operation that stores and indexes content. However, it does not disclose whether files are overwritten, error handling, or required permissions, which could be valuable.

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?

Description is concise and well-structured: a single-sentence purpose, followed by clear args, returns, and examples. Every sentence adds value, no fluff.

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 purpose, args, returns, and examples. With an output schema present, the return format is already documented. Lacks details on size limits or allowed file types, but overall sufficient for a save operation.

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

Parameters5/5

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

Schema has 0% coverage, but description fully compensates by explaining the 'content' param as file content and 'path' as full path including filename with examples. This adds essential meaning beyond the raw schema.

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?

Description clearly states the tool saves artifacts (user-created content like diagrams, notes, code) to storage, and indexes them for search. It distinguishes from siblings like retrieve_artifact and delete_artifact by focusing on creation/saving.

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 clear context that it saves content to organized file structures, but lacks explicit guidance on when to use this tool versus alternatives like 'store' or 'save_context'. No 'when not to use' or conditions provided.

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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