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run_build

Compile projects using detected languages like Go, Rust, TypeScript, or Python with language-specific commands. Returns build success status and error details without arbitrary shell execution.

Instructions

Compile the project at workspace_dir using the detected workspace language. Language-specific dispatch (no arbitrary shell execution): go build ./..., cargo build, tsc --noEmit, mypy . (Python typecheck proxy). Optional path param narrows scope. Returns: { success: bool, errors: [{file, line, column, message}], raw: string }. Does not require start_lsp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_dirYes
pathNo
languageNo
Behavior4/5

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

With no annotations provided, the description carries full burden and does well. It discloses that it's a compilation/type checking operation (implies mutation of build artifacts), specifies language-specific dispatch (no arbitrary shell execution), describes the return format including success flag and error details, and mentions it doesn't require LSP. However, it doesn't mention potential side effects like creating build files or performance implications.

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 efficiently structured in three sentences: first states purpose with examples, second explains optional parameter, third describes returns and LSP relationship. Every sentence adds value with no redundancy or fluff.

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

Completeness4/5

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

For a 3-parameter tool with no annotations and no output schema, the description is quite complete. It covers purpose, parameters, return format, and distinguishes from siblings. The main gap is lack of explicit error handling details or performance characteristics, but given the context, it provides sufficient guidance for agent usage.

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?

With 0% schema description coverage for 3 parameters, the description compensates well. It explains workspace_dir is for the project location, path narrows scope optionally, and language is detected automatically (though the parameter exists). It doesn't specify format constraints for workspace_dir or path, or valid values for language, leaving some gaps.

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 clearly states the tool compiles projects at a workspace directory using detected languages, with specific examples (go build, cargo build, tsc, mypy). It distinguishes from siblings like start_lsp by explicitly stating 'Does not require start_lsp' and differs from run_tests by focusing on compilation/type checking rather than testing.

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 clear context for when to use this tool: for compiling projects in supported languages. It explicitly mentions an alternative (start_lsp) to avoid, but doesn't specify when to choose between run_build and other build-related siblings if they exist, or when path narrowing is appropriate versus using the full workspace.

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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