dev_explain_failure

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

No annotations are provided, so the description carries the full burden. It discloses that the tool 'cross-references project type, runtimes, services, ports, and dependencies' and that it 'ranks likely root causes with evidence'. It also clarifies a behavioral trait: 'never asserting certainty beyond the evidence'. This is transparent about the tool's inductive reasoning and its limitation. The description doesn't mention any destructive actions or side effects, but the name suggests (and the description confirms) it is purely diagnostic. Given the lack of annotations, this is a good level of transparency.

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 two sentences long, with the main purpose and inputs at the front. It packs a lot of information: the input, the cross-referencing behavior, the output (ranked root causes with evidence), and a critical limitation ('never asserting certainty beyond the evidence'). No fluff, every clause earns its place. The structure is clear: first sentence states the action, second expands on internals and output.

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 (diagnostic reasoning tool with multiple input parameters and an output schema), the description covers the core functionality well: it explains what the tool does, what it takes, and what it returns. The output schema exists (though not provided in the input schema here, but the signal says 'Has output schema: true'), so the description doesn't need to detail return values. The main missing piece is explicit mention of the 'workspace' parameter – it is implied by 'project type, runtimes, services' but not directly stated as an input. Other than that, the description is complete enough for an agent to invoke the tool correctly.

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 for the parameters. The description mentions 'error/output text' and 'command that produced it' and 'workspace' implicitly. It doesn't explicitly name the workspace parameter, but it says 'cross-references project type, runtimes, services, ports, and dependencies' which implies the workspace is the project context. The description adds value by explaining what the parameters are used for (error_message as the primary input, command as optional context). It does not cover all parameter semantics in detail (e.g., format of workspace), but given the high-level nature, it provides enough meaning beyond the schema's bare property names.

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: diagnose a development failure. It specifies the inputs (error/output text, optionally the command) and the output (ranks likely root causes with evidence). The verb 'diagnose' and the resource 'development failure' are specific, and the description distinguishes it from siblings by focusing on failure analysis rather than detection, health, or project info.

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 explicitly tells the agent when to use this tool: when you have error/output text and optionally the command that produced it. It implies that the tool is for diagnosing failures, not for general health checks or detection. While it doesn't explicitly name alternatives, the context signals and sibling names (dev_check, dev_detect) suggest it's for failure analysis, and the description gives a clear condition for invocation. This is a strong usage guideline, essentially 'use this when you have error text and want root cause analysis'.

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