Agent skill

Analyse Problem

by NeoLabHQ in NeoLabHQ/context-engineering-kit

Comprehensive A3 one-page problem analysis with root cause and action plan

GPL-3.0Auto-check passedDevelopment

Install Analyse Problem

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyse-problem .claude/skills/analyse-problem && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .claude/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyse-problem .agents/skills/analyse-problem && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .agents/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyse-problem .cursor/skills/analyse-problem && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .cursor/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/NeoLabHQ/context-engineering-kit.git --path skills/analyse-problem

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyse-problem .gemini/skills/analyse-problem && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .gemini/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyse-problem .github/skills/analyse-problem && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .github/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install NeoLabHQ/context-engineering-kit analyse-problem --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyse-problem .opencode/skills/analyse-problem && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "analyse-problem" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/analyse-problem into .opencode/skills/analyse-problem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyse-problem", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: analyse-problem
GitHub stars: 1.7k
Token cost: ~5.3k tokens
SKILL.md length: 213 words
Files: 1
Skills in repo: 57
Repo updated: Aug 26, 2026
First seen: Oct 8, 2026
Licence: GPL-3.0

At a glance

Comprehensive A3 one-page problem analysis with root cause and action plan

Works in 7 steps: Background: Why this problem matters… → Current Condition: What's happening now… → Goal/Target: What success looks like… → …
Tasks that involve Root cause analysis
SKILL.md covers Description, Usage, Variables and Steps, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analyse Problem is an agent skill from NeoLabHQ/context-engineering-kit. Comprehensive A3 one-page problem analysis with root cause and action plan

Its SKILL.md is about 5.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Root cause analysis. The repository describes itself as: Hand-crafted Claude Code Skills focused on improving agent results quality. Compatible with OpenCode, Cursor, Antigravity, Gemini CLI, and others. Includes CodeRabbit open-source… The licence is GPL-3.0.

When your agent uses it

Tasks that involve Root cause analysis

Example prompts

“/analyse-problem”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

Background: Why this problem matters (context, business impact)
Current Condition: What's happening now (data, metrics, examples)
Goal/Target: What success looks like (specific, measurable)
Root Cause Analysis: Why problem exists (use 5 Whys or Fishbone)
Countermeasures: Proposed solutions addressing root causes
Implementation Plan: Who, what, when, how
Follow-up: How to verify success and prevent recurrence

What it can do on your machine

Read from SKILL.md and the folder at commit 23e2428. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyse Problem loads about 5.3k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 213 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~23
When it runs · the whole SKILL.md, loaded when a task matches: ~5.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NeoLabHQ/context-engineering-kit at commit 23e2428, republished under its GPL-3.0 licence (© NeoLabHQ). 213 words, ~5,282 tokens.

Download SKILL.mdSave it as .claude/skills/analyse-problem/SKILL.md (or your agent's skills folder).

name: analyse-problem
description: Comprehensive A3 one-page problem analysis with root cause and action plan

A3 Problem Analysis

Apply A3 problem-solving format for comprehensive, single-page problem documentation and resolution planning.

Description

Structured one-page analysis format covering: Background, Current Condition, Goal, Root Cause Analysis, Countermeasures, Implementation Plan, and Follow-up. Named after A3 paper size; emphasizes concise, complete documentation.

Usage

/analyse-problem [problem_description]

Variables

PROBLEM: Issue to analyze (default: prompt for input)
OUTPUT_FORMAT: markdown or text (default: markdown)

Steps

Background: Why this problem matters (context, business impact)
Current Condition: What's happening now (data, metrics, examples)
Goal/Target: What success looks like (specific, measurable)
Root Cause Analysis: Why problem exists (use 5 Whys or Fishbone)
Countermeasures: Proposed solutions addressing root causes
Implementation Plan: Who, what, when, how
Follow-up: How to verify success and prevent recurrence

A3 Template

═══════════════════════════════════════════════════════════════
                    A3 PROBLEM ANALYSIS
═══════════════════════════════════════════════════════════════

TITLE: [Concise problem statement]
OWNER: [Person responsible]
DATE: [YYYY-MM-DD]

┌─────────────────────────────────────────────────────────────┐
│ 1. BACKGROUND (Why this matters)                            │
├─────────────────────────────────────────────────────────────┤
│ [Context, impact, urgency, who's affected]                  │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 2. CURRENT CONDITION (What's happening)                     │
├─────────────────────────────────────────────────────────────┤
│ [Facts, data, metrics, examples - no opinions]              │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 3. GOAL/TARGET (What success looks like)                    │
├─────────────────────────────────────────────────────────────┤
│ [Specific, measurable, time-bound targets]                  │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 4. ROOT CAUSE ANALYSIS (Why problem exists)                 │
├─────────────────────────────────────────────────────────────┤
│ [5 Whys, Fishbone, data analysis]                           │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 5. COUNTERMEASURES (Solutions addressing root causes)       │
├─────────────────────────────────────────────────────────────┤
│ [Specific actions, not vague intentions]                    │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 6. IMPLEMENTATION PLAN (Who, What, When)                    │
├─────────────────────────────────────────────────────────────┤
│ [Timeline, responsibilities, dependencies, milestones]      │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 7. FOLLOW-UP (Verification & Prevention)                    │
├─────────────────────────────────────────────────────────────┤
│ [Success metrics, monitoring plan, review dates]            │
└─────────────────────────────────────────────────────────────┘

═══════════════════════════════════════════════════════════════

Examples

Example 1: Database Connection Pool Exhaustion

═══════════════════════════════════════════════════════════════
                    A3 PROBLEM ANALYSIS
═══════════════════════════════════════════════════════════════

TITLE: API Downtime Due to Connection Pool Exhaustion
OWNER: Backend Team Lead
DATE: 2024-11-14

┌─────────────────────────────────────────────────────────────┐
│ 1. BACKGROUND                                                │
├─────────────────────────────────────────────────────────────┤
│ • API goes down 2-3x per week during peak hours             │
│ • Affects 10,000+ users, average 15min downtime             │
│ • Revenue impact: ~$5K per incident                         │
│ • Customer satisfaction score dropped from 4.5 to 3.8       │
│ • Started 3 weeks ago after traffic increased 40%           │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 2. CURRENT CONDITION                                         │
├─────────────────────────────────────────────────────────────┤
│ Observations:                                                │
│ • Connection pool size: 10 (unchanged since launch)         │
│ • Peak concurrent users: 500 (was 300 three weeks ago)      │
│ • Average request time: 200ms (was 150ms)                   │
│ • Connections leaked: ~2 per hour (never released)          │
│ • Error: "Connection pool exhausted" in logs                │
│                                                              │
│ Pattern:                                                     │
│ • Occurs at 2pm-4pm daily (peak traffic)                    │
│ • Gradual degradation over 30 minutes                       │
│ • Recovery requires app restart                             │
│ • Long-running queries block pool (some 30+ seconds)        │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 3. GOAL/TARGET                                               │
├─────────────────────────────────────────────────────────────┤
│ • Zero downtime due to connection exhaustion                │
│ • Support 1000 concurrent users (2x current peak)           │
│ • All connections released within 5 seconds                 │
│ • Achieve within 1 week                                     │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 4. ROOT CAUSE ANALYSIS                                       │
├─────────────────────────────────────────────────────────────┤
│ 5 Whys:                                                      │
│ Problem: Connection pool exhausted                          │
│ Why 1: All 10 connections in use, none available            │
│ Why 2: Connections not released after requests              │
│ Why 3: Error handling doesn't close connections             │
│ Why 4: Try-catch blocks missing .finally()                  │
│ Why 5: No code review checklist for resource cleanup        │
│                                                              │
│ Contributing factors:                                        │
│ • Pool size too small for current load                      │
│ • No connection timeout configured (hangs forever)          │
│ • Slow queries hold connections longer                      │
│ • No monitoring/alerting on pool metrics                    │
│                                                              │
│ ROOT CAUSE: Systematic issue with resource cleanup +        │
│             insufficient pool sizing                         │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 5. COUNTERMEASURES                                           │
├─────────────────────────────────────────────────────────────┤
│ Immediate (This Week):                                       │
│ 1. Audit all DB code, add .finally() for connection release │
│ 2. Increase pool size: 10 → 30                              │
│ 3. Add connection timeout: 10 seconds                       │
│ 4. Add pool monitoring & alerts (>80% used)                 │
│                                                              │
│ Short-term (2 Weeks):                                        │
│ 5. Optimize slow queries (add indexes)                      │
│ 6. Implement connection pooling best practices doc          │
│ 7. Add automated test for connection leaks                  │
│                                                              │
│ Long-term (1 Month):                                         │
│ 8. Migrate to connection pool library with auto-release     │
│ 9. Add linter rule detecting missing .finally()             │
│ 10. Create PR checklist for resource management             │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 6. IMPLEMENTATION PLAN                                       │
├─────────────────────────────────────────────────────────────┤
│ Week 1 (Nov 14-18):                                          │
│ • Day 1-2: Audit & fix connection leaks [Dev Team]          │
│ • Day 2: Increase pool size, add timeout [DevOps]           │
│ • Day 3: Set up monitoring [SRE]                            │
│ • Day 4: Test under load [QA]                               │
│ • Day 5: Deploy to production [DevOps]                      │
│                                                              │
│ Week 2 (Nov 21-25):                                          │
│ • Optimize identified slow queries [DB Team]                │
│ • Write best practices doc [Tech Writer + Dev Lead]         │
│ • Create connection leak test [QA Team]                     │
│                                                              │
│ Week 3-4 (Nov 28 - Dec 9):                                   │
│ • Evaluate connection pool libraries [Dev Team]             │
│ • Add linter rules [Dev Lead]                               │
│ • Update PR template [Dev Lead]                             │
│                                                              │
│ Dependencies: None blocking Week 1 fixes                     │
│ Resources: 2 developers, 1 DevOps, 1 SRE                    │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 7. FOLLOW-UP                                                 │
├─────────────────────────────────────────────────────────────┤
│ Success Metrics:                                             │
│ • Zero downtime incidents (monitor 4 weeks)                 │
│ • Pool usage stays <80% during peak                         │
│ • No connection leaks detected                              │
│ • Response time <200ms p95                                  │
│                                                              │
│ Monitoring:                                                  │
│ • Daily: Check pool usage dashboard                         │
│ • Weekly: Review connection leak alerts                     │
│ • Bi-weekly: Team retrospective on progress                 │
│                                                              │
│ Review Dates:                                                │
│ • Week 1 (Nov 18): Verify immediate fixes effective         │
│ • Week 2 (Nov 25): Assess optimization impact               │
│ • Week 4 (Dec 9): Final review, close A3                    │
│                                                              │
│ Prevention:                                                  │
│ • Add connection handling to onboarding                     │
│ • Monthly audit of resource management code                 │
│ • Include pool metrics in SRE runbook                       │
└─────────────────────────────────────────────────────────────┘

═══════════════════════════════════════════════════════════════

Example 2: Security Vulnerability in Production

═══════════════════════════════════════════════════════════════
                    A3 PROBLEM ANALYSIS
═══════════════════════════════════════════════════════════════

TITLE: Critical SQL Injection Vulnerability
OWNER: Security Team Lead
DATE: 2024-11-14

┌─────────────────────────────────────────────────────────────┐
│ 1. BACKGROUND                                                │
├─────────────────────────────────────────────────────────────┤
│ • Critical security vulnerability reported by researcher    │
│ • SQL injection in user search endpoint                     │
│ • Potential data breach affecting 100K+ user records        │
│ • CVSS score: 9.8 (Critical)                                │
│ • Vulnerability exists in production for 6 months           │
│ • Similar issue found in 2 other endpoints (scanning)       │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 2. CURRENT CONDITION                                         │
├─────────────────────────────────────────────────────────────┤
│ Vulnerable Code:                                             │
│ • /api/users/search endpoint uses string concatenation      │
│ • Input: search query (user-provided, not sanitized)        │
│ • Pattern: `SELECT * FROM users WHERE name = '${input}'`    │
│                                                              │
│ Scope:                                                       │
│ • 3 endpoints vulnerable (search, filter, export)           │
│ • All use same unsafe pattern                               │
│ • No parameterized queries                                  │
│ • No input validation layer                                 │
│                                                              │
│ Risk Assessment:                                             │
│ • Exploitable from public internet                          │
│ • No evidence of exploitation (logs checked)                │
│ • Similar code in admin panel (higher privilege)            │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 3. GOAL/TARGET                                               │
├─────────────────────────────────────────────────────────────┤
│ • Patch all SQL injection vulnerabilities within 24 hours   │
│ • Zero SQL injection vulnerabilities in codebase            │
│ • Prevent similar issues in future code                     │
│ • Verify no unauthorized access occurred                    │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 4. ROOT CAUSE ANALYSIS                                       │
├─────────────────────────────────────────────────────────────┤
│ 5 Whys:                                                      │
│ Problem: SQL injection vulnerability in production          │
│ Why 1: User input concatenated directly into SQL            │
│ Why 2: Developer wasn't aware of SQL injection risks        │
│ Why 3: No security training for new developers              │
│ Why 4: Security not part of onboarding checklist            │
│ Why 5: Security team not involved in development process    │
│                                                              │
│ Contributing Factors (Fishbone):                             │
│ • Process: No security code review                          │
│ • Technology: ORM not used consistently                     │
│ • People: Knowledge gap in secure coding                    │
│ • Methods: No SAST tools in CI/CD                           │
│                                                              │
│ ROOT CAUSE: Security not integrated into development        │
│             process, training gap                            │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 5. COUNTERMEASURES                                           │
├─────────────────────────────────────────────────────────────┤
│ Immediate (24 Hours):                                        │
│ 1. Patch all 3 vulnerable endpoints                         │
│ 2. Deploy hotfix to production                              │
│ 3. Scan codebase for similar patterns                       │
│ 4. Review access logs for exploitation attempts             │
│                                                              │
│ Short-term (1 Week):                                         │
│ 5. Replace all raw SQL with parameterized queries           │
│ 6. Add input validation middleware                          │
│ 7. Set up SAST tool in CI (Snyk/SonarQube)                  │
│ 8. Security team review of all data access code             │
│                                                              │
│ Long-term (1 Month):                                         │
│ 9. Mandatory security training for all developers           │
│ 10. Add security review to PR process                       │
│ 11. Migrate to ORM for all database access                  │
│ 12. Implement security champion program                     │
│ 13. Quarterly security audits                               │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 6. IMPLEMENTATION PLAN                                       │
├─────────────────────────────────────────────────────────────┤
│ Hour 0-4 (Emergency Response):                               │
│ • Write & test patches [Security + Senior Dev]              │
│ • Emergency PR review [CTO + Tech Lead]                     │
│ • Deploy to staging [DevOps]                                │
│                                                              │
│ Hour 4-24 (Production Deploy):                               │
│ • Deploy hotfix [DevOps + On-call]                          │
│ • Monitor for issues [SRE Team]                             │
│ • Scan logs for exploitation [Security Team]                │
│ • Notify stakeholders [Security Lead + CEO]                 │
│                                                              │
│ Day 2-7:                                                     │
│ • Full codebase remediation [Dev Team]                      │
│ • SAST tool setup [DevOps + Security]                       │
│ • Security review [External Auditor]                        │
│                                                              │
│ Week 2-4:                                                    │
│ • Security training program [Security + HR]                 │
│ • Process improvements [Engineering Leadership]             │
│                                                              │
│ Dependencies: External auditor availability (Week 2)         │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 7. FOLLOW-UP                                                 │
├─────────────────────────────────────────────────────────────┤
│ Success Metrics:                                             │
│ • Zero SQL injection vulnerabilities (verified by scan)     │
│ • 100% of PRs pass SAST checks                              │
│ • 100% developer security training completion               │
│ • No unauthorized access detected in log analysis           │
│                                                              │
│ Verification:                                                │
│ • Day 1: Verify patch deployed, vulnerability closed        │
│ • Week 1: External security audit confirms fixes            │
│ • Week 2: SAST tool catching similar issues                 │
│ • Month 1: Training completion, process adoption            │
│                                                              │
│ Prevention:                                                  │
│ • SAST tools block vulnerable code in CI                    │
│ • Security review required for data access code             │
│ • Quarterly penetration testing                             │
│ • Annual security training refresh                          │
│                                                              │
│ Incident Report:                                             │
│ • Post-mortem meeting: Nov 16                               │
│ • Document lessons learned                                  │
│ • Share with engineering org                                │
└─────────────────────────────────────────────────────────────┘

═══════════════════════════════════════════════════════════════

Notes

A3 forces concise, complete thinking (fits on one page)
Use data and facts, not opinions or blame
Root cause analysis is critical—use /why or /cause-and-effect
Countermeasures must address root causes, not symptoms
Implementation plan needs clear ownership and timelines
Follow-up ensures sustainable improvement
A3 becomes historical record for organizational learning
Update A3 as situation evolves (living document until closed)
Consider A3 for: incidents, recurring issues, major improvements
Overkill for: small bugs, one-line fixes, trivial issues

Files

Just SKILL.md in skills/analyse-problem of NeoLabHQ/context-engineering-kit.

Open the folder on GitHubat commit 23e2428

Compare with similar skills

Analyse Problem next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analyse Problem compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Analyse Problem this skillNeoLabHQ/context-engineering-kit	1.7k	—	~5.3k	Automated safety check: Pass	GPL-3.0	1 mo ago
Code Design Rationale Investigatorcursor/plugins	10k	9 repos	~2.6k	Automated safety check: Pass	None	yesterday
OpenLogi macOS Permissions TriageAprilNEA/OpenLogi	23k	—	~2.5k	Automated safety check: Notes	Apache-2.0	today
Bug Finder for daisyUIsaadeghi/daisyui	43k	—	~2.3k	Automated safety check: Pass	MIT	yesterday
Root Cause Debugginggarrytan/gstack	136k	—	~1.4k	Automated safety check: Pass	MIT	today
Review PRapache/shardingsphere	21k	—	~6.4k	Automated safety check: Pass	Apache-2.0	today

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Review an existing GitHub pull request and post inline review comments on its diff.
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Questions about Analyse Problem

What does Analyse Problem do?

Comprehensive A3 one-page problem analysis with root cause and action plan. Analyse Problem is an agent skill from NeoLabHQ/context-engineering-kit.

When should I use Analyse Problem?

Analyse Problem fits situations like: tasks that involve Root cause analysis.

How do I install Analyse Problem in Claude Code?

Run `npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a claude-code`. Or copy the skill folder (skills/analyse-problem in NeoLabHQ/context-engineering-kit) into .claude/skills/analyse-problem in your project. Claude Code loads it when a task matches its description.

How do I install Analyse Problem in Codex?

Run `npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a codex`. Or copy the skill folder (skills/analyse-problem in NeoLabHQ/context-engineering-kit) into .agents/skills/analyse-problem in your project. Codex loads it when a task matches its description.

Can I use Analyse Problem in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeoLabHQ/context-engineering-kit --skill analyse-problem -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyse-problem, .gemini/skills/analyse-problem, .github/skills/analyse-problem and .opencode/skills/analyse-problem in your project.

What does Analyse Problem need to run?

SKILL.md names no scripts, command-line tools or credentials: Analyse Problem is instructions for the agent only.

Does Analyse Problem access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyse Problem safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Analyse Problem use?

Analyse Problem is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyse Problem use?

About 5.3k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Analyse Problem?

Skills that share tags, products or a category with Analyse Problem: Code Design Rationale Investigator (cursor/plugins, 10k stars), OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars), Bug Finder for daisyUI (saadeghi/daisyui, 43k stars) and Root Cause Debugging (garrytan/gstack, 136k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyse Problem?

NeoLabHQ (a GitHub organization) maintains it in NeoLabHQ/context-engineering-kit, which has 1,749 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on August 26, 2026.

Source: NeoLabHQ/context-engineering-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Analyse Problem

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At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

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Context cost

Safety

SKILL.md

A3 Problem Analysis

Description

Usage

Variables

Steps

A3 Template

Examples

Example 1: Database Connection Pool Exhaustion

Example 2: Security Vulnerability in Production

Notes

Files

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Similar skills

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