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run_workflow

Run a named multi-agent pipeline for feature shipping, PR triage, or parallel local/cloud work. Each step receives prior output, so agents coordinate sequentially or combine results in parallel.

Instructions

Run a named multi-agent pipeline. Built-in: ship-feature (planner → builder → reviewer), troubleshoot-pr (pr-triage → builder → reviewer), local-and-cloud (vLLM + Cursor cloud in parallel), cloud-with-local-draft (vLLM draft then cloud builder). Each sequential step sees prior output. Parallel recipes collect both results. Local file writes still require an allowed cwd. Cloud agents never call localhost vLLM.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNo
taskYesUser goal or PR description
branchNo
pr_urlNo
repo_urlNo
workflowYesWorkflow id from list_agents
extra_contextNo
stop_on_errorNoDefault true
Behavior4/5

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

With no annotations, the description carries the full behavioral disclosure burden, and it does so substantively: it reveals that sequential steps see prior output, parallel recipes collect both results, local writes require an allowed cwd, and cloud agents never call localhost vLLM. It does not disclose the return model (e.g., whether a run ID is returned synchronously or how to poll), which keeps this from a 5.

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 compact and front-loaded: purpose first, then workflow options, then behavioral constraints. Every sentence carries useful information with no filler or repetition of schema details, achieving high information density in under 100 words.

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

Completeness2/5

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

This is a complex multi-agent orchestration tool with 8 parameters and no output schema, yet the description says nothing about the return value, run lifecycle, or how to retrieve results. Sibling tools like get_run and list_runs hint at a run model, but the description itself leaves an agent without enough information to know what happens after invocation.

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

Parameters3/5

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

Schema description coverage is only 38%, so the description needed to compensate for undocumented parameters. It adds real value for 'workflow' by listing built-in option names and for 'cwd' by noting the allowed-directory requirement. However, branch, pr_url, repo_url, and extra_context remain unexplained in both schema and description, leaving a significant gap.

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 opens with a specific verb+resource: 'Run a named multi-agent pipeline.' It then enumerates four concrete built-in workflows (ship-feature, troubleshoot-pr, local-and-cloud, cloud-with-local-draft), making the tool's scope unmistakable and clearly distinguishing it from simpler sibling tools like dispatch or vllm_status.

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 gives clear contextual guidance by listing the built-in recipes and explaining sequential vs. parallel execution behavior. It does not explicitly contrast run_workflow with alternatives like dispatch or chat_send, so exclusions and when-not-to-use guidance are missing, but an agent can infer the intended use case from the named pipeline framing.

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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