software_spot_weld_fix

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: conservative defaults (preview mode on, PR on, deploy off) and routing with approval gates for production/cloud fixes. It explicitly states 'rather than direct mutation,' clarifying the non-destructive nature. While it doesn't cover all behaviors (e.g., rate limits, idempotency), it effectively communicates the tool's safety and routing.

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 extremely concise, consisting of two sentences and a brief note on defaults. It front-loads the main purpose and adds essential details about behavior without any fluff. Every sentence contributes meaning, making it easy for an agent to parse quickly.

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?

Given the tool's complexity (14 parameters, 2 required) and the presence of an output schema, the description covers the core request purpose, default behavior, and routing but lacks details on prerequisites, error scenarios, or the expected output format. It is adequate but not thorough, especially for a tool that initiates a workflow potentially involving approvals and deployments.

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?

The schema description coverage is 0%, so the description must compensate. It adds semantic context for four parameters (preview_mode, open_pr, trigger_deploy, auto_push) by explaining their conservative defaults. However, it does not discuss the remaining 10 parameters (e.g., request, workspace_id, repository), leaving their meaning entirely to self-explanatory names. This is insufficient for a 14-parameter tool.

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 purpose: 'Request a bounded urgent production/cloud fix through the Lightbulb loop.' It specifies the verb (request), the resource (urgent fix), and the mechanism (Lightbulb loop). The name 'software_spot_weld_fix' is distinct among siblings, and the description differentiates it from general software development tools by emphasizing urgency and production/cloud impact.

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 provides clear context on when to use: for urgent production/cloud fixes that require approval gates and are not direct mutations. It implies that this tool is for bounded, urgent scenarios where conservative defaults are appropriate. However, it does not explicitly mention when not to use or name alternative tools, which prevents a score of 5.

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