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save_artifact

Store completed research, analyses, code, or documentation as searchable files with metadata and tags, preserving significant work for later retrieval and collaboration.

Instructions

Save a research artifact (finding, analysis, summary) to the session.

AUTOMATIC TRIGGERS - Call this when:

  • You complete a significant analysis or research summary

  • You've written important code or documentation

  • You want to save a detailed analysis (beyond a simple message)

  • Completing a major deliverable

Use this for SIGNIFICANT work products, not for inline messages. Artifacts are stored as files with metadata indexed in SQLite.

WORKFLOW POSITION: Call after completing substantial work.

PARAMETERS:

  • session_id: Target session

  • title: Descriptive title for the artifact

  • content: Full artifact content (markdown recommended)

  • created_by: Your agent ID

  • artifact_type: Type like 'research_summary', 'analysis', 'code', 'data'

  • tags: Tags for categorization

  • shared: If True, save to shared directory (default: False)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
titleYes
sharedNo
contentYes
created_byYes
session_idYes
artifact_typeNo
Behavior3/5

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

With no annotations provided, the description carries the behavioral transparency burden. It usefully discloses that artifacts are stored as files with metadata indexed in SQLite and that shared=True saves to a shared directory. However, it does not mention overwrite behavior, return value, idempotency, or potential failure modes, which would be valuable for a write tool.

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?

The description is well-structured with clear sections for triggers, workflow position, and parameters, making it easy to scan. There is minor redundancy between 'AUTOMATIC TRIGGERS' and 'WORKFLOW POSITION', but overall each section earns its place.

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?

The description provides enough context for an agent to decide when to use the tool and how to fill parameters. It lacks output schema information and does not clarify the relationship with save_finding, but for a save operation the provided details are largely sufficient.

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 0%, so the description must compensate, and it does. All seven parameters are listed with concise but meaningful explanations, including artifact_type examples and the effect of shared=True. This adds value beyond the raw 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 the tool saves a research artifact (finding, analysis, summary) to the session, with specific examples and automatic trigger conditions. It is unambiguous about the action and resource, though it does not explicitly distinguish itself from the sibling save_finding tool.

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

Usage Guidelines4/5

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

The description provides explicit trigger conditions for when to call the tool, including completing significant analysis, writing important code/documentation, and saving detailed analyses. It also gives a clear exclusion ('not for inline messages'), though it does not mention alternative tools like save_finding for comparison.

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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