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export_to_library

After a session ends, preserve artifacts and summaries as searchable findings in the OpenLMlib library so future projects can retrieve and reuse them.

Instructions

Export session artifacts as findings in the main OpenLMLib library.

AUTOMATIC TRIGGERS - Call this when:

  • A collaboration session is completed

  • You want to persist session work to the main knowledge base

  • Future sessions might need this knowledge

After a session completes, use this to permanently store the research outputs in the main library for future retrieval.

WORKFLOW POSITION: After session termination, before starting new work.

PARAMETERS:

  • session_id: Completed session to export

  • agent_id: Orchestrator agent ID authorizing the export

  • project: Project name for findings (defaults to session title)

  • confidence: Default confidence 0.0-1.0 (default: 0.8)

  • tags: Additional tags to apply to all findings

  • artifact_ids: Specific artifacts to export (None = all)

  • include_summary: Also export the session summary as a finding (default: True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
projectNo
agent_idNo
confidenceNo
session_idYes
artifact_idsNo
include_summaryNo
Behavior3/5

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

With no annotations, the description carries the burden, and it adds useful behavioral context: the operation 'permanently store' and 'Afer a session completes' indicates persistence and timing. However, it does not disclose potential side effects, authorization needs, idempotency, or error behavior, so it only partially covers behavioral transparency.

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 front-loaded with a one-sentence purpose, then organized into trigger bullets, workflow position, and parameter list. It is slightly repetitive ('Afer a session completes' appears twice), 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.

Completeness3/5

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

Given 7 params, no output schema, no annotations, and many similar sibling tools (save_finding, save_finding_auto, export_co_scientist_findings), the description covers triggers, workflow position, and params but does not distinguish from those siblings or explain what the call returns. It is adequate but leaves routing and return behavior missing.

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?

The description includes a dedicated PRAAMETERS section explaining the meaning and defaults for all 7 parameters, e.g., 'artifacts_ids: Specific artifacts to export (None = all)' and 'project: Project name for findings (defaults to session title)'. This exceeds the schema, which has 0% description coverage, by adding functional semantics and defaults context.

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 states a specific verb and resource: 'Export session artifacts as findings in the main OpenLMLib library.' The explicit mention of session artifacts and main library differentiates it from generic save_finding and export_co_scientist_findings, and the automatic-trigger context reinforces its scope.

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 'AUTOMATIC TRIGGERS' with conditions like 'A collaboration session is completed' and workflow position 'Afer session termination, before starting new work.' It lacks explicit alternatives or when-not-to-use guidance, hence not a 5.

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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