debugger

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

The description discloses that the tool 'fans out to the configured provider panel' with a specific persona, that each provider needs key/CLI and rate limits apply. This adds behavioral context beyond the annotations (readOnlyHint=true, destructiveHint=false, openWorldHint=true). No contradictions with annotations; the description provides useful transparency about external dependencies and response format.

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: first clearly states the purpose and output, second provides usage guidance and behavioral notes. It is concise with no unnecessary words, effectively front-loading the key information. Every sentence earns its place.

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 (debugging analysis using external providers), the description covers purpose, usage, behavioral notes (provider dependency, rate limits), and output format. It mentions return structure (JSON envelope with results array) but does not detail the results schema, which is acceptable without an output schema. Generally complete for effective use.

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 input schema has 6 parameters with 100% description coverage, so the schema already explains each parameter. The description does not add new meaning beyond what the schema provides (e.g., it doesn't elaborate on how 'prompt' should be structured for best results). Baseline score of 3 is appropriate since the schema carries the burden.

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 is a debugging specialist that produces ranked root-cause hypotheses and small safe fixes from bug reports, logs, and code. It specifies the output format (JSON envelope with results array) and when to use it (crashes, failing tests, wrong output). This distinguishes it from sibling tools like 'code-reviewer' or 'researcher', which have different focus areas.

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 says 'Use for crashes, failing tests, or wrong output', providing clear usage context. It does not explicitly state when not to use, but the tool's name and specialization implicitly exclude other tasks. It mentions the tool returns 'says honestly that the evidence shows no bug', which guides appropriate usage. No direct comparison to alternatives, but the scope is reasonably defined.

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