run_agent_across_list

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: parallel processing ('batches of 10 parallel processes'), permission skipping ('automatic permission skipping enabled'), output handling ('Output streams directly to files'), completion behavior ('waits for all agents to complete before returning'), and post-completion steps ('Read the stdout files...'). However, it lacks details on error handling beyond checking stderr files, such as retry logic or failure modes.

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 well-structured with clear sections (e.g., 'WHEN TO USE', 'AVAILABLE AGENTS', 'HOW IT WORKS'), making it easy to scan. It is appropriately sized for a complex tool, with each sentence adding useful information. However, some redundancy exists (e.g., permission-skipping mentioned multiple times), slightly reducing efficiency.

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?

For a complex tool with no annotations and no output schema, the description provides comprehensive context: purpose, usage guidelines, behavioral details, parameter usage, and post-execution steps. It covers the tool's workflow and dependencies (e.g., requires a previously created list). The main gap is the lack of output schema, but the description compensates by explaining output handling and file naming conventions.

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 100%, so the schema already documents all parameters. The description adds value by explaining variable substitution ('Use {{item}} in your prompt') with examples, clarifying how 'prompt' interacts with list items. It also lists available agents with details on their permission-skipping behaviors, enhancing understanding beyond the enum in the schema. However, it doesn't add significant context for 'list_id' beyond what the schema states.

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 explicitly states the tool's purpose: 'Spawns an AI coding agent for each item in a previously created list.' It specifies the verb ('spawns'), resource ('AI coding agent'), and scope ('for each item in a previously created list'), clearly distinguishing it from sibling tools like 'run_shell_across_list' which handles shell commands rather than AI agents.

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 'WHEN TO USE' section provides explicit guidance: 'Performing complex code analysis, refactoring, or generation across multiple files,' 'Tasks that require AI reasoning rather than simple shell commands,' and 'When you need to delegate work to multiple AI agents working in parallel.' It also implicitly contrasts with 'run_shell_across_list' by emphasizing AI reasoning over shell commands.

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