problem-solving

Structured problem-solving framework with specialized agents for research, analysis, architecture decisions, validation, synthesis, reviews, investigations, and reporting. Use when tackling complex problems that need systematic exploration, evidence-based decisions, and persistent artifacts.

16 stars

Best use case

problem-solving is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Structured problem-solving framework with specialized agents for research, analysis, architecture decisions, validation, synthesis, reviews, investigations, and reporting. Use when tackling complex problems that need systematic exploration, evidence-based decisions, and persistent artifacts.

Teams using problem-solving should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/problem-solving/SKILL.md --create-dirs "https://raw.githubusercontent.com/geekatron/jerry/main/skills/problem-solving/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/problem-solving/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How problem-solving Compares

Feature / Agentproblem-solvingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Structured problem-solving framework with specialized agents for research, analysis, architecture decisions, validation, synthesis, reviews, investigations, and reporting. Use when tackling complex problems that need systematic exploration, evidence-based decisions, and persistent artifacts.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Problem-Solving Skill

> **Version:** 2.2.0
> **Framework:** Jerry Problem-Solving (PS)
> **Constitutional Compliance:** Jerry Constitution v1.0

## Document Audience (Triple-Lens)

This SKILL.md serves multiple audiences:

| Level | Audience | Sections to Focus On |
|-------|----------|---------------------|
| **L0 (ELI5)** | New users, stakeholders | [Purpose](#purpose), [When to Use](#when-to-use-this-skill), [Routing Disambiguation](#routing-disambiguation), [Quick Reference](#quick-reference) |
| **L1 (Engineer)** | Developers invoking agents | [Invoking an Agent](#invoking-an-agent), [Agent Details](#agent-details), [Adversarial Quality Mode](#adversarial-quality-mode) |
| **L2 (Architect)** | Workflow designers | [Orchestration Flow](#orchestration-flow), [State Passing](#state-passing-between-agents), [Adversarial Quality Mode](#adversarial-quality-mode) |

---

## Purpose

The Problem-Solving skill provides a structured framework for tackling complex problems through specialized agents. Each agent produces **persistent artifacts** that survive context compaction and build a knowledge base over time.

### Key Capabilities

- **Structured Research** - Gather and document findings with source citations
- **Deep Analysis** - Root cause analysis, trade-offs, gap analysis, risk assessment
- **Architecture Decisions** - ADRs using Nygard format with L0/L1/L2 explanations
- **Validation** - Constraint verification with traceability matrices
- **Synthesis** - Cross-document pattern extraction and knowledge generation
- **Reviews** - Code, design, architecture, and security quality assessment
- **Investigations** - Failure analysis using 5 Whys, Ishikawa, FMEA
- **Reporting** - Status reports with health metrics and progress tracking

---

## When to Use This Skill

Activate when:

- Starting research on a new technology or approach
- Analyzing a problem to find root causes
- Making architectural decisions that need documentation
- Validating that constraints are satisfied
- Synthesizing findings across multiple documents
- Reviewing code, designs, or architecture
- Investigating failures or incidents
- Generating status or progress reports

---

## Available Agents

| Agent | Role | Output Location |
|-------|------|-----------------|
| `ps-researcher` | Research Specialist - Gathers information with citations | `docs/research/` |
| `ps-analyst` | Analysis Specialist - Deep analysis (5 Whys, FMEA, trade-offs) | `docs/analysis/` |
| `ps-architect` | Architecture Specialist - Creates ADRs with Nygard format | `docs/decisions/` |
| `ps-critic` | **Quality Evaluator - Iterative refinement with quality scores** | `docs/critiques/` |
| `ps-validator` | Validation Specialist - Verifies constraints with evidence | `docs/analysis/` |
| `ps-synthesizer` | Synthesis Specialist - Pattern extraction across documents | `docs/synthesis/` |
| `ps-reviewer` | Review Specialist - Code/design/security quality reviews | `docs/reviews/` |
| `ps-investigator` | Investigation Specialist - Root cause of failures | `docs/investigations/` |
| `ps-reporter` | Reporting Specialist - Status and progress reports | `docs/reports/` |

All agents produce output at three levels:
- **L0 (ELI5):** Executive summary for non-technical stakeholders
- **L1 (Software Engineer):** Technical implementation details
- **L2 (Principal Architect):** Strategic implications and trade-offs

---

## Invoking an Agent

### Option 1: Natural Language Request

Simply describe what you need:

```
"Research best practices for event sourcing in Python"
"Analyze the trade-offs between SQLite and PostgreSQL for this use case"
"Create an ADR for choosing Redis as our caching layer"
"Validate that all domain constraints are met"
"Investigate why the API timeout occurred"
```

The orchestrator will select the appropriate agent based on keywords and context.

### Option 2: Explicit Agent Request

Request a specific agent:

```
"Use ps-researcher to explore graph database options"
"Have ps-analyst do a 5 Whys on the login failures"
"I need ps-architect to create an ADR for the new persistence layer"
```

### Option 3: Task Tool Invocation

For programmatic invocation within workflows:

```python
Task(
    description="ps-researcher: Graph databases",
    subagent_type="general-purpose",
    prompt="""
You are the ps-researcher agent (v2.0.0).

## PS CONTEXT (REQUIRED)
- **PS ID:** work-024
- **Entry ID:** e-101
- **Topic:** Graph Database Options

## MANDATORY PERSISTENCE (P-002)
Create file at: docs/research/work-024-e-101-graph-databases.md

## RESEARCH TASK
Research graph database options for the Jerry framework.
Focus on: Gremlin compatibility, Python support, embedded options.
"""
)
```

---

## Orchestration Flow

### Sequential Chain Example

For complex problems requiring multiple perspectives:

```
User Request: "I need to understand why our tests are slow and fix it"

1. ps-researcher → Gather data on test execution patterns
   Output: docs/research/work-024-e-001-test-performance.md

2. ps-analyst → Apply 5 Whys to identify root cause
   Output: docs/analysis/work-024-e-002-root-cause.md

3. ps-architect → Create ADR for proposed solution
   Output: docs/decisions/work-024-e-003-adr-test-optimization.md

4. ps-validator → Verify solution meets constraints
   Output: docs/analysis/work-024-e-004-validation.md
```

### State Passing Between Agents

Agents can reference each other's output using state keys:

| Agent | Output Key | Provides |
|-------|------------|----------|
| ps-researcher | `researcher_output` | Research findings, sources |
| ps-analyst | `analyst_output` | Root cause, recommendations |
| ps-architect | `architect_output` | Decision, alternatives |
| ps-validator | `validator_output` | Validation status, gaps |
| ps-synthesizer | `synthesizer_output` | Patterns, themes |
| ps-reviewer | `reviewer_output` | Findings, assessment |
| ps-investigator | `investigator_output` | Root cause, corrective actions |
| ps-reporter | `reporter_output` | Metrics, health status |

---

## Tool Invocation Examples

Each agent uses the allowed tools differently. Here are concrete examples:

### Research Tasks (ps-researcher)

```
1. Find existing research documents:
   Glob(pattern="docs/research/**/*.md")
   → Returns list of prior research to reference

2. Search for industry sources:
   WebSearch(query="event sourcing Python patterns 2026")
   → Find current industry guidance

3. Create research output (MANDATORY per P-002):
   Write(
       file_path="docs/research/work-024-e-001-event-sourcing.md",
       content="# Research: Event Sourcing in Python\n\n## L0: Executive Summary\n..."
   )
   → Persist findings - transient output VIOLATES P-002
```

### Analysis Tasks (ps-analyst)

```
1. Find prior analyses to reference:
   Glob(pattern="docs/analysis/**/*.md")

2. Search for specific patterns in codebase:
   Grep(pattern="try|except|raise", path="src/", output_mode="content", -C=2)
   → Find error handling patterns for root cause analysis

3. Read existing documentation:
   Read(file_path="docs/research/work-024-e-001-event-sourcing.md")
   → Load prior research to inform analysis

4. Create analysis output (MANDATORY per P-002):
   Write(
       file_path="docs/analysis/work-024-e-002-root-cause.md",
       content="# Root Cause Analysis: Build Failures\n\n## L0: Executive Summary\n..."
   )
```

### Architecture Tasks (ps-architect)

```
1. Find existing ADRs for consistency:
   Glob(pattern="docs/decisions/**/*.md")
   → Reference prior decisions

2. Research architectural patterns:
   WebFetch(url="https://martinfowler.com/eaaDev/EventSourcing.html",
            prompt="Extract key benefits and trade-offs of event sourcing")

3. Create ADR output (MANDATORY per P-002):
   Write(
       file_path="docs/decisions/work-024-e-003-adr-persistence.md",
       content="# ADR-042: Use Event Sourcing for Task History\n\n## Status\nPROPOSED\n..."
   )
```

---

## Mandatory Persistence (P-002)

All agents MUST persist their output to files. This ensures:

1. **Context Rot Resistance** - Findings survive session compaction
2. **Knowledge Accumulation** - Artifacts build project knowledge base
3. **Auditability** - Decisions can be traced and reviewed
4. **Collaboration** - Outputs can be shared and referenced

### Output Structure

```
docs/
├── research/           # ps-researcher outputs
│   └── {ps-id}-{entry-id}-{topic}.md
├── analysis/           # ps-analyst and ps-validator outputs
│   └── {ps-id}-{entry-id}-{analysis-type}.md
├── decisions/          # ps-architect ADRs
│   └── {ps-id}-{entry-id}-adr-{slug}.md
├── synthesis/          # ps-synthesizer outputs
│   └── {ps-id}-{entry-id}-synthesis.md
├── reviews/            # ps-reviewer outputs
│   └── {ps-id}-{entry-id}-{review-type}.md
├── investigations/     # ps-investigator outputs
│   └── {ps-id}-{entry-id}-investigation.md
└── reports/            # ps-reporter outputs
    └── {ps-id}-{entry-id}-{report-type}.md
```

---

## Adversarial Quality Mode

> **SSOT Reference:** `.context/rules/quality-enforcement.md` -- all thresholds, strategy IDs, and criticality levels are defined there. NEVER hardcode values; always reference the SSOT.

The problem-solving skill integrates the adversarial quality framework defined in EPIC-002. This enables structured creator-critic-revision cycles with strategy-specific adversarial review for all PS workflows.

### Strategy Catalog

The quality framework provides 10 selected adversarial strategies across 4 mechanistic families. See `.context/rules/quality-enforcement.md` (Strategy Catalog section) for the authoritative list with IDs S-001 through S-014, composite scores, and family classifications.

| Family | Strategies | PS Application |
|--------|-----------|----------------|
| **Iterative Self-Correction** | S-014 (LLM-as-Judge), S-007 (Constitutional AI Critique), S-010 (Self-Refine) | Quality scoring, constitutional compliance checks, self-review before output |
| **Dialectical Synthesis** | S-003 (Steelman Technique) | Strengthening arguments before critique, ensuring balanced analysis |
| **Role-Based Adversarialism** | S-002 (Devil's Advocate), S-004 (Pre-Mortem Analysis), S-001 (Red Team Analysis) | Challenging assumptions, anticipating failures, adversarial exploration |
| **Structured Decomposition** | S-013 (Inversion Technique), S-012 (FMEA), S-011 (Chain-of-Verification) | Systematic failure mode analysis, verification chains, inverse reasoning |

### Creator-Critic-Revision Cycle

Per H-14 (HARD rule), all C2+ deliverables MUST go through a minimum 3-iteration creator-critic-revision cycle.

**Cycle flow:**
1. **Creator** (any PS agent) produces deliverable
2. **Critic** (ps-critic, ps-reviewer, or MAIN CONTEXT) evaluates using S-014 (LLM-as-Judge) with dimension-level rubrics
3. **Revision** -- creator revises based on critic feedback
4. Repeat until quality threshold is met or circuit breaker triggers

**Quality scoring** uses the 6-dimension weighted composite defined in the SSOT:
- Completeness (0.20), Internal Consistency (0.20), Methodological Rigor (0.20), Evidence Quality (0.15), Actionability (0.15), Traceability (0.10)
- Threshold: >= 0.92 weighted composite for C2+ deliverables (H-13)
- Scoring mechanism: S-014 (LLM-as-Judge) with active leniency bias counteraction

**Circuit breaker:** Minimum 3 iterations REQUIRED (H-14). If no improvement after 2 consecutive iterations, ACCEPT_WITH_CAVEATS or escalate to user.

### Criticality-Based Activation

Strategy activation follows the SSOT criticality levels (C1-C4). See `.context/rules/quality-enforcement.md` (Criticality Levels section) for the authoritative mapping.

| Level | PS Context | Required Strategies | Typical PS Scenario |
|-------|-----------|---------------------|---------------------|
| **C1 (Routine)** | Simple research, status reports | S-010 (Self-Refine) | Single-topic research, progress report |
| **C2 (Standard)** | Analysis, design decisions, reviews | S-007, S-002, S-014 | Root cause analysis, ADR creation, code review |
| **C3 (Significant)** | Architecture decisions, cross-cutting analysis | C2 + S-004, S-012, S-013 | Multi-system impact analysis, architecture ADR |
| **C4 (Critical)** | Governance, irreversible decisions | All 10 selected strategies | Constitution changes, governance decisions |

**Auto-escalation rules** (AE-001 through AE-006 in the SSOT) apply to PS workflows. Key rules:
- AE-001: PS artifacts touching `docs/governance/JERRY_CONSTITUTION.md` = auto-C4
- AE-002: PS artifacts touching `.context/rules/` = auto-C3 minimum
- AE-003: New or modified ADR = auto-C3 minimum

### PS-Specific Strategy Selection

When selecting adversarial strategies for PS workflows, use these context-based recommendations:

| PS Task Type | Primary Strategy | Supporting Strategies | Rationale |
|-------------|------------------|----------------------|-----------|
| **Research** (ps-researcher) | S-011 (CoVe) | S-003 (Steelman), S-010 (Self-Refine) | Verify claims, strengthen findings, self-check |
| **Root Cause Analysis** (ps-analyst) | S-013 (Inversion) | S-004 (Pre-Mortem), S-012 (FMEA) | Challenge causal chain, anticipate failures |
| **Architecture Decisions** (ps-architect) | S-002 (Devil's Advocate) | S-003 (Steelman), S-004 (Pre-Mortem), S-014 (LLM-as-Judge) | Challenge assumptions, strengthen rationale, score quality |
| **Synthesis** (ps-synthesizer) | S-003 (Steelman) | S-013 (Inversion), S-014 (LLM-as-Judge) | Strengthen patterns, invert assumptions, score quality |
| **Code/Design Review** (ps-reviewer) | S-001 (Red Team) | S-007 (Constitutional AI), S-012 (FMEA) | Adversarial exploration, compliance check, failure modes |
| **Quality Critique** (ps-critic) | S-014 (LLM-as-Judge) | S-003 (Steelman), S-007 (Constitutional AI) | Structured scoring, balanced assessment, compliance |

### Mandatory Self-Review (H-15)

Per H-15 (HARD rule), all PS agents MUST perform self-review using S-010 (Self-Refine) before presenting any deliverable. This applies regardless of criticality level.

Per H-16 (HARD rule), agents MUST apply S-003 (Steelman Technique) before critiquing -- strengthen the argument first, then challenge it.

---

## Constitutional Compliance

All agents adhere to the **Jerry Constitution v1.0**:

| Principle | Requirement | Consequence of Violation |
|-----------|-------------|-------------------------|
| P-003 | NEVER spawn recursive subagents -- max 1 level | Agent hierarchy violation; uncontrolled token consumption |
| P-020 | NEVER override user intent -- ask before destructive ops | Unauthorized action; trust erosion |
| P-022 | NEVER deceive about actions, capabilities, or confidence | Governance undermined; quality assessment invalidated |
| P-001 | NEVER present findings without evidence or source citations | Unreliable outputs; unfounded claims propagate downstream |
| P-002 | NEVER leave outputs in transient context only -- persist to files | Context rot vulnerability; artifacts lost on session compaction |
| P-004 | NEVER omit reasoning provenance or source documentation | Untraceable decisions; audit trail broken |
| P-011 | NEVER make recommendations without supporting evidence | Unsupported recommendations; confidence inflated without basis |

---

## Quick Reference

### Common Workflows

| Need | Agent | Command Example |
|------|-------|-----------------|
| Research a topic | ps-researcher | "Research OAuth2 implementation patterns" |
| Find root cause | ps-analyst | "Analyze why builds are failing" |
| Document a decision | ps-architect | "Create ADR for choosing PostgreSQL" |
| Verify constraints | ps-validator | "Validate domain layer constraints" |
| Find patterns | ps-synthesizer | "Synthesize findings from the 3 research docs" |
| Review code quality | ps-reviewer | "Review the new authentication module" |
| Investigate incident | ps-investigator | "Investigate the production outage" |
| Status report | ps-reporter | "Generate phase status report" |

### Agent Selection Hints

| Keywords | Likely Agent |
|----------|--------------|
| research, explore, find, gather, investigate options | ps-researcher |
| analyze, root cause, trade-off, gap, risk, 5 whys, FMEA | ps-analyst |
| ADR, architecture decision, design, choose, decide | ps-architect |
| validate, verify, constraint, test, evidence | ps-validator |
| synthesize, patterns, themes, combine, meta-analysis | ps-synthesizer |
| review, quality, code review, security, OWASP | ps-reviewer |
| investigate, failure, incident, debug, what happened | ps-investigator |
| report, status, progress, metrics, summary | ps-reporter |

---

## Templates

Problem-solving artifacts should use standardized templates to ensure consistency.

**Location:** `docs/knowledge/exemplars/templates/`

| Template | Use For | Path |
|----------|---------|------|
| `adr.md` | Architecture Decision Records | `docs/knowledge/exemplars/templates/adr.md` |
| `research.md` | Research artifacts | `docs/knowledge/exemplars/templates/research.md` |
| `analysis.md` | Analysis artifacts | `docs/knowledge/exemplars/templates/analysis.md` |
| `deep-analysis.md` | Deep analysis | `docs/knowledge/exemplars/templates/deep-analysis.md` |
| `synthesis.md` | Synthesis documents | `docs/knowledge/exemplars/templates/synthesis.md` |
| `review.md` | Review artifacts | `docs/knowledge/exemplars/templates/review.md` |
| `investigation.md` | Investigation reports | `docs/knowledge/exemplars/templates/investigation.md` |
| `jrn.md` | Journal entries | `docs/knowledge/exemplars/templates/jrn.md` |
| `use-case-template.md` | Use case specifications | `docs/knowledge/exemplars/templates/use-case-template.md` |

**Usage:** When creating a new artifact, read the appropriate template first to ensure consistent structure and sections.

---

## Routing Disambiguation

> When this skill is the wrong choice and what happens if misrouted.

| Condition | Use Instead | Consequence of Misrouting |
|-----------|-------------|--------------------------|
| Simple multi-agent workflow coordination without research | `/orchestration` | Problem-solving loads 9 agent definitions (ps-researcher, ps-analyst, ps-architect, ps-critic, ps-validator, ps-synthesizer, ps-reviewer, ps-investigator, ps-reporter) when task only needs workflow state tracking and checkpoint coordination |
| Requirements engineering, V&V, or formal technical reviews (SRR/PDR/CDR) | `/nasa-se` | Problem-solving produces research artifacts and ADRs; NASA SE traceability matrices, VCRM tables, and NPR-compliant review packages not generated |
| Transcript parsing or meeting note extraction (VTT/SRT files) | `/transcript` | Problem-solving has no VTT/SRT parser; transcript-specific agents (ts-parser, ts-extractor) with hybrid Python+LLM architecture not invoked |
| Standalone adversarial quality review or tournament scoring | `/adversary` | Problem-solving ps-critic operates within creator-critic-revision loops (H-14); standalone one-shot adversarial assessment with strategy template selection requires /adversary |
| Security-hardened software design or threat modeling | `/eng-team` | Problem-solving lacks STRIDE/DREAD methodology, OWASP ASVS verification, and NIST SSDF governance; security-specific agent team (10 agents) not loaded |
| Offensive security testing or penetration testing | `/red-team` | Problem-solving produces research artifacts, not attack narratives; no MITRE ATT&CK kill chain coverage or engagement authorization methodology |
| Work item tracking or entity management | `/worktracker` | Problem-solving has no entity hierarchy management; WORKTRACKER.md manifest operations and WTI integrity rules not available |

---

## Agent Details

For detailed agent specifications, see:

- `skills/problem-solving/agents/ps-researcher.md`
- `skills/problem-solving/agents/ps-analyst.md`
- `skills/problem-solving/agents/ps-architect.md`
- `skills/problem-solving/agents/ps-validator.md`
- `skills/problem-solving/agents/ps-synthesizer.md`
- `skills/problem-solving/agents/ps-reviewer.md`
- `skills/problem-solving/agents/ps-investigator.md`
- `skills/problem-solving/agents/ps-reporter.md`

---

*Skill Version: 2.2.0*
*Constitutional Compliance: Jerry Constitution v1.0*
*Enhancement: EN-707 Adversarial quality mode integration (EPIC-003)*
*Last Updated: 2026-02-14*

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16
from geekatron/jerry

Atomic Design component taxonomy sub-skill for the /user-experience parent skill. Implements Brad Frost's 5-level component hierarchy (Atoms, Molecules, Organisms, Templates, Pages) for design system architecture. Produces component inventories, design token audits, composition rules, and Storybook coverage reports. Invoke when teams need component taxonomy construction, design system architecture, Storybook integration, design token consistency analysis, or component reuse auditing. Invoked by ux-orchestrator during Wave 3 lifecycle-stage routing or when user intent is "Building component system" during the "During design" stage. Triggers: atomic design, component taxonomy, design tokens, Storybook, atoms molecules organisms, design system, component inventory, component library.

ux-ai-first-design

16
from geekatron/jerry

AI-first interaction design sub-skill (CONDITIONAL) for the /user-experience parent skill. Provides trust-calibrated AI interaction design guidance using Yang et al.'s trust-risk and error-risk classification framework. Produces interaction pattern recommendations, trust calibration assessments, feedback loop designs, and progressive disclosure strategies for AI-powered features. CONDITIONAL: requires WSM >= 7.80 AND enabler research (FEAT-020) complete; otherwise routes to /ux-heuristic-eval with PAIR protocol. Invoke when teams need to design AI-powered interactions, calibrate user trust in AI outputs, classify AI error risks, design human-AI handoff patterns, or audit existing AI interfaces for trust and safety. Triggers: AI-first design, AI interaction, trust calibration, AI UX, conversational UX, AI interface, LLM interface, agentic UX, human-AI interaction, AI transparency, AI error handling, AI onboarding, progressive AI disclosure, trust-risk, error-risk.

user-experience

16
from geekatron/jerry

Parent orchestrator for AI-augmented UX methodology targeting tiny teams (1-5 people). Routes to 10 sub-skills by product lifecycle stage through criteria-gated waves. Invoke when team needs structured UX evaluation, user research, design systems, UX metrics, behavior diagnosis, feature prioritization, design sprints, or AI interaction design. Each sub-skill implements a proven UX framework with synthesis hypothesis confidence gates and MCP design tool integration. Triggers: UX, user experience, usability, heuristic evaluation, JTBD, lean UX, HEART metrics, atomic design, inclusive design, behavior design, Kano model, design sprint, AI-first design, UX audit, accessibility, design system, user research.

use-case

16
from geekatron/jerry

Guided use case authoring and decomposition using Cockburn's 12-step writing process and Jacobson UC 2.0 progressive narrative levels. Creates structured use case artifacts with YAML frontmatter validated against use-case-realization-v1.schema.json. Decomposes use cases into implementation-ready slices with INVEST criteria verification and produces realization interaction sequences for downstream /test-spec and /contract-design consumption. Invoke when writing, creating, authoring, elaborating, slicing, decomposing, or realizing use cases.