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llm_pipeline_templates

Browse pipeline templates for multi-step AI orchestration across 20+ providers with automatic model routing, cost control, and fallback chains.

Instructions

List available pipeline templates for multi-step orchestration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description carries full burden. While 'List' implies read-only, the description does not disclose caching behavior, network requirements, rate limits, or whether templates are static or dynamic. Minimal behavioral context.

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?

Single sentence of 7 words with action-fronted structure ('List available...'). Zero redundancy or waste. Every word 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?

Adequate for a zero-parameter tool with output schema present, but lacks domain context about what these pipeline templates contain or their relationship to the orchestration system. Minimum viable given complexity.

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?

Input schema contains 0 parameters with 100% coverage. Per scoring rules, 0 parameters warrants a baseline score of 4. No additional parameter semantics are needed or provided.

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?

Uses specific verb 'List' with resource 'pipeline templates' and provides domain context 'multi-step orchestration' that distinguishes it from execution-focused siblings like llm_orchestrate. However, it does not explicitly contrast with related tools.

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?

Provides no guidance on when to use this tool versus alternatives like llm_orchestrate (which likely executes pipelines) or when listing is preferable to other operations. No prerequisites or conditions mentioned.

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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