Creates structured debugging plans with hypotheses, experiments, and logging instrumentation to pinpoint root causes from given symptoms.
Create debugging hypotheses, experiments, and logging or instrumentation plan
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Model | |
| context | No | Context | |
| symptom | Yes | Symptom | |
| provider | No | Provider | auto |
| constraints | No | Constraints | |
| preview_only | No | Preview only |
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining behavior. It only lists outputs ('hypotheses, experiments, and logging or instrumentation plan') and does not disclose whether 'create' means generating a returned plan, persisting state, calling a model, or whether 'preview_only' alters side effects.
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 a single sentence, front-loaded with the verb and main deliverables. It is appropriately compact, although the list of outputs is somewhat dense and could be structured with clearer separation.
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 tool with six parameters, no annotations, and no output schema, the description is too thin to give an agent complete guidance. It does not explain expected return values, how constraints or provider affect the plan, or what 'preview_only' controls, leaving important call-time decisions ambiguous.
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 baseline is 3 even though the description adds no parameter detail. The schema's property descriptions are terse ('Symptom', 'Model', 'Provider'), but the description itself does not enrich or clarify any parameter semantics beyond what the schema already provides.
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 uses a specific verb ('Create') and identifies the resource: debugging hypotheses, experiments, and a logging/instrumentation plan. It is clear enough to suggest a debugging-oriented planning tool, though it does not explicitly distinguish itself from sibling planning tools like coeus_test_strategy or coeus_eval_plan.
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 word 'debugging' and the required 'symptom' parameter imply this tool is for investigating a bug symptom, providing some usage context. However, there is no explicit statement of when to use it versus similar sibling tools, nor any exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.