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save_artifact

Store complete research artifacts linked to a conversation. After saving the conversation transcript, save each artifact (report, table, code) with its full content to preserve high-value outputs as searchable objects.

Instructions

Save a single artifact (research report, table, framework, spec, code) linked to a conversation memory.

WHEN TO USE: After calling save_conversation for a session that produced artifacts. Call this ONCE PER ARTIFACT with the full verbatim content — do NOT summarize or truncate.

WHY: Artifacts are the highest-value output of research sessions. Saving them separately ensures complete preservation. Each artifact becomes a first-class searchable object linked to its parent conversation.

FLOW:

  1. save_conversation(title="Research Session", conversationId="my-research") → saves the conversation transcript

  2. save_artifact(conversationId="my-research", title="Competitive Analysis", type="research", content="")

  3. save_artifact(conversationId="my-research", title="Ranking Table", type="table", content="")

IMPORTANT: Send the COMPLETE artifact content in the content field. The entire point of this tool is to preserve artifacts that would otherwise be lost or summarized. Minimum 100 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversationIdYesThe conversationId of the parent memory to link this artifact to. Must match the conversationId used in save_conversation.
titleYesTitle of this artifact (e.g., "Competitive Analysis Report", "Architecture Ranking Table", "Implementation Spec")
typeYesType of artifact
contentYesCOMPLETE artifact content — the full verbatim text, not a summary.
tagsNoOptional tags for categorization
Behavior4/5

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

Annotations are present (readOnlyHint: false, destructiveHint: false, openWorldHint: true). The description adds context about artifacts being high-value and becoming searchable objects, which goes beyond the annotations. It 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.

Conciseness5/5

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

The description is well-structured with clear sections (short statement, WHEN TO USE, WHY, FLOW, IMPORTANT). It is front-loaded with key information and every part serves a purpose without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the parameter count, required fields, no output schema, and annotations, the description fully covers purpose, usage flow, parameter details, and importance. An agent can effectively use the tool based on this description.

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 100%, so baseline is 3. The description adds semantics for conversationId (must match save_conversation), content (full verbatim, not summary), and provides examples for title and type. This adds value beyond the 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?

The description clearly states the tool saves a single artifact linked to a conversation memory, with a specific verb and resource. It distinguishes from siblings like save_conversation and save_investigation_result by focusing on artifacts.

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

Usage Guidelines5/5

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

The description provides explicit WHEN TO USE guidelines, stating it should be called after save_conversation, once per artifact, with full content. It includes a FLOW example and explicit instructions not to summarize or truncate.

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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