Run a sequential AI pipeline

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

With no annotations provided, the description must carry the behavioral burden, and it does: it explains the sequential chaining behavior, that each step uses a chosen AI provider, and that step output becomes the next step's input via {{input}}. It does not mention error handling, return format, or provider-specific behavior, but the core execution model is clearly disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, dense sentence with no filler. It front-loads the primary action ('Runs a sequential pipeline') and then immediately explains the key mechanics, earning every clause without redundancy.

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

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

The description covers the pipeline's flow and variable substitution, which are essential. But given the absence of an output schema and annotations, it omits what the tool returns, whether errors occur mid-pipeline, and what happens if a step fails. This is a moderate gap for a multi-step execution tool.

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

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

Schema description coverage is 50%, and the description adds meaning by explaining how {{input}} works in promptTemplate and that outputs flow between steps. However, it does not clarify the semantics of the steps array elements (e.g., provider, model, system) beyond what the schema already provides, leaving some gap for low-coverage parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Runs a sequential pipeline' with each step handled by an AI provider and outputs feeding into the next. This distinguishes it from list-type siblings like list_providers and list_models, but it does not explicitly contrast with run_orchestrator or run_debate beyond the sequential chaining concept.

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

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

The description implies usage for sequential multi-step AI processing through terms like 'sequential pipeline' and 'feeds into the next step's input.' However, it provides no explicit guidance on when to choose this over sibling tools such as run_orchestrator or run_debate, nor any exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.