Investigate problem, verify findings, and derive solutions
Installation
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Investigate problem, verify findings, and derive solutions
disable-model-invocation
true
Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Context: Diagnosis flow to identify root cause and present solutions
Target problem: $ARGUMENTS
Orchestrator Definition
Core Identity: "I am not a worker. I am an orchestrator."
Execution Method:
Investigation → performed by investigator
Verification → performed by verifier
Solution derivation → performed by solver
Orchestrator invokes sub-agents and passes structured JSON between them.
Task Registration: Register execution steps using TaskCreate and proceed systematically. Update status using TaskUpdate.
Step 0: Problem Structuring (Before investigator invocation)
0.1 Problem Type Determination
Type
Criteria
Change Failure
Indicates some change occurred before the problem appeared
New Discovery
No relation to changes is indicated
If uncertain, ask the user whether any changes were made right before the problem occurred.
0.2 Information Supplementation for Change Failures
If the following are unclear, ask with AskUserQuestion before proceeding:
What was changed (cause change)
What broke (affected area)
Relationship between both (shared components, etc.)
0.3 Problem Essence Understanding
Invoke rule-advisor via Agent tool:
subagent_type: rule-advisor
description: "Problem essence analysis"
prompt: Identify the essence and required rules for this problem: [Problem reported by user]
Confirm from rule-advisor output:
taskAnalysis.mainFocus: Primary focus of the problem
mandatoryChecks.taskEssence: Root problem beyond surface symptoms
selectedRules: Applicable rule sections
warningPatterns: Patterns to avoid
0.4 Reflecting in investigator Prompt
Include the following in investigator prompt:
Problem essence (taskEssence)
Key applicable rules summary (from selectedRules)
Investigation focus (investigationFocus): Convert warningPatterns to "points prone to confusion or oversight in this investigation"
For change failures, additionally include:
Detailed analysis of the change content
Commonalities between cause change and affected area
Determination of whether the change is a "correct fix" or "new bug" with comparison baseline selection
Context Separation: Pass only structured JSON output to each step. Each step starts fresh with the JSON data only.
Execution Steps
Register the following using TaskCreate and execute:
Step 1: Investigation (investigator)
Agent tool invocation:
subagent_type: investigator
description: "Investigate problem"
prompt: |
Comprehensively collect information related to the following phenomenon.
Phenomenon: [Problem reported by user]
Problem essence: [taskEssence from Step 0.3]
Investigation focus: [investigationFocus from Step 0.4]
[For change failures, additionally include:]
Change details: [What was changed]
Affected area: [What broke]
Shared components: [Commonalities between cause and effect]
Expected output: pathMap (execution paths per symptom), failurePoints (faults found at each node), impactAnalysis per failure point, unexplored areas, investigation limitations
Step 2: Investigation Quality Check
Review investigation output:
Quality Check (verify JSON output contains the following):
pathMap exists with at least one symptom, and each symptom has at least one path with nodes listed
Each failure point has: location, upstreamDependency, symptomExplained, causalChain (reaching a stop condition), checkStatus, evidence with a source citing a specific file or location
Each failure point has comparisonAnalysis (normalImplementation found or explicitly null)
causeCategory for each failure point is one of: typo / logic_error / missing_constraint / design_gap / external_factor
investigationSources covers at least 3 distinct source types (code, history, dependency, config, document, external)
Investigation covers investigationFocus items (when provided in Step 0.4)
All nodes on mapped paths have been checked (no path was abandoned after finding the first fault)
If quality insufficient: Re-run investigator specifying missing items explicitly:
prompt: |
Re-investigate with focus on the following gaps:
- Missing: [list specific missing items from quality check]
Previous investigation results (for context, do not re-investigate covered areas):
[Previous investigation JSON]
design_gap Escalation:
When investigator output contains causeCategory: design_gap or recurrenceRisk: high:
Insert user confirmation before verifier execution
Use AskUserQuestion:
"A design-level issue was detected. How should we proceed?"
A: Attempt fix within current design
B: Include design reconsideration
If user selects B, pass includeRedesign: true to solver
Proceed to verifier once quality is satisfied.
Step 3: Verification (verifier)
Agent tool invocation:
subagent_type: verifier
description: "Verify investigation results"
prompt: Verify the following investigation results.
Investigation results: [Investigation JSON output]
Expected output: Coverage check (missing paths, unchecked nodes), Devil's Advocate evaluation per failure point, failure point evaluation with checkStatus, coverage assessment
Coverage Criteria:
sufficient: Main paths traced, all critical nodes checked, each failure point individually evaluated
partial: Main paths traced, some nodes unchecked or some failure points at blocked/not_reached
insufficient: Significant paths untraced, or critical nodes not investigated
Step 4: Solution Derivation (solver)
Agent tool invocation:
subagent_type: solver
description: "Derive solutions"
prompt: Derive solutions based on the following verified failure points.
Confirmed failure points: [verifier's conclusion.confirmedFailurePoints]
Refuted failure points: [verifier's conclusion.refutedFailurePoints]
Failure point relationships: [verifier's conclusion.failurePointRelationships]
Impact analysis: [investigator's impactAnalysis]
Coverage assessment: [sufficient/partial/insufficient]
Expected output: Multiple solutions (at least 3), tradeoff analysis, recommendation and implementation steps, residual risks