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debugging_approach

Troubleshoot software issues using structured debugging methodologies, including hypothesis tracking, evidence collection, and root cause analysis.

Instructions

Systematic debugging methodologies for troubleshooting and problem resolution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issueYesA detailed and specific description of the problem, including observed vs. expected behavior, and steps to reproduce if known.
stepsNoDebugging steps taken, either as simple strings or detailed step objects.
toolsNoTools and technologies used during debugging.
methodNoDetailed information about the debugging method being used.
endTimeNoWhen the debugging session ended.
evidenceNoEvidence collected during the debugging process.
findingsNoThe key observations, data points, or discoveries made during the debugging process.
sessionIdNoUnique identifier for this debugging session.
startTimeNoWhen the debugging session started.
aiAnalysisNoAI-powered analysis results for enhanced debugging capabilities.
hypothesesNoHypotheses about potential causes of the issue.
resolutionNoA clear explanation of the final fix, including any code changes, configuration updates, or other actions taken.
approachNameYesThe name of the systematic debugging method being applied (e.g., 'Log Analysis', 'Delta Debugging', 'Root Cause Analysis').
participantsNoPeople involved in the debugging process.
documentationNoDocumentation of the debugging process and resolution.
effectivenessNoMetrics for evaluating the effectiveness of the debugging approach.
totalDurationNoTotal time spent debugging.
classificationNoStructured classification of the issue.
lessonsLearnedNoKey lessons learned from this debugging session.
preventionMeasuresNoMeasures to prevent similar issues in the future.
Behavior2/5

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

No annotations are present, so the description must convey behavioral traits. It does not mention that the tool likely creates/updates a debugging session, nor does it disclose side effects, required permissions, or whether it is read-only or write. The agent gets no insight into tool impact.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise, but it lacks substance. It prioritizes brevity over informativeness. The structure is front-loaded with the purpose, but the content is too vague to be effective.

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

Completeness2/5

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

Given the tool has 20 parameters, nested objects, no output schema, and many siblings, the description is far too minimal. It does not explain the tool's role in the debugging workflow, what it returns, or how it complements related tools. The agent is left guessing about its integration.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with detailed parameter descriptions. The tool description adds no additional meaning beyond the schema. Baseline score of 3 applies as the description neither enhances nor detracts from parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Systematic debugging methodologies for troubleshooting and problem resolution' is generic. It indicates a debugging focus but lacks a specific verb or resource to distinguish what the tool actually does (e.g., record, apply, guide). Among sibling tools like scientific_method or decision_framework, the purpose is not well differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description does not state prerequisites, typical scenarios, or when not to use it. For a tool with many siblings, this omission reduces clarity.

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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