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Agent skill

Sector Analyst

by nicepkg in nicepkg/ai-workflow

This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns.

MITAuto-check passedMarketing & SEO

Install Sector Analyst

skills CLI
$ npx skills add nicepkg/ai-workflow --skill sector-analyst -a claude-code

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

GitHub CLI
$ gh skill install nicepkg/ai-workflow sector-analyst --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/nicepkg/ai-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/stock-trader-workflow/.claude/skills/sector-analyst .claude/skills/sector-analyst && 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/

Facts

Skill name
sector-analyst
GitHub stars
285
Token cost
~2.1k tokens
SKILL.md length
794 words
Files
5 (incl. references, assets)
Skills in repo
75
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns.

  • Works in 5 steps: Data Collection and Observation → Market Cycle Assessment → Current Situation Analysis → …
  • The user provides performance chart images (1-week
  • SKILL.md covers Overview, When to Use This Skill, Analysis Workflow and Output Format, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Sector Analyst is an agent skill from nicepkg/ai-workflow. This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files and assets (for example `references/sector_rotation.md`).

It sits in Marketing & SEO, covering Positioning and messaging. The repository describes itself as: 🚀 170+ pre-built skills for Claude Code, Cursor, Codex & 14+ AI tools. Stop re-teaching your AI the same things. One command → instant domain expertise. Marketing, SEO, Trading… The licence is MIT.

When your agent uses it

  • The user provides performance chart images (1-week
  • 1-month timeframes) for sectors
  • Industries and requests market cycle assessment
  • Sector rotation analysis

Example prompts

  • “/sector-analyst”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Data Collection and Observation
  2. Market Cycle Assessment
  3. Current Situation Analysis
  4. Scenario Development
  5. Output Generation

What it can do on your machine

Read from SKILL.md and the folder at commit d167b41. 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 (its code samples are markdown).

    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

Sector Analyst loads about 2.1k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 112 tokens; SKILL.md has 794 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~112
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

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 nicepkg/ai-workflow at commit d167b41, republished under its MIT licence (© nicepkg). 794 words, ~2,087 tokens.

Download SKILL.mdSave it as .claude/skills/sector-analyst/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
sector-analyst
description
This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.

Sector Analyst

Overview

This skill enables comprehensive analysis of sector and industry performance charts to identify market cycle positioning and predict likely rotation scenarios. The analysis combines observed performance data with established sector rotation principles to provide objective market assessment and probabilistic scenario forecasting.

When to Use This Skill

Use this skill when:

  • User provides sector performance charts (typically 1-week and 1-month timeframes)
  • User provides industry performance charts showing relative performance data
  • User requests analysis of current market cycle positioning
  • User asks for sector rotation assessment or predictions
  • User needs probability-weighted scenarios for market positioning

Example user requests:

  • "Analyze these sector performance charts and tell me where we are in the market cycle"
  • "Based on these performance charts, what sectors should outperform next?"
  • "What's the probability of a defensive rotation based on this data?"
  • "Review these sector and industry charts and provide scenario analysis"

Analysis Workflow

Follow this structured workflow when analyzing sector/industry performance charts:

Step 1: Data Collection and Observation

First, carefully examine all provided chart images to extract:

  • Sector-level performance: Identify which sectors (Technology, Financials, Consumer Discretionary, etc.) are outperforming/underperforming
  • Industry-level performance: Note specific industries showing strength or weakness
  • Timeframe comparison: Compare 1-week vs 1-month performance to identify trend consistency or divergence
  • Magnitude of moves: Assess the size of relative performance differences
  • Breadth of movement: Determine if performance is concentrated or broad-based

Think in English while analyzing the charts. Document specific numerical performance figures for key sectors and industries.

Step 2: Market Cycle Assessment

Load the sector rotation knowledge base to inform analysis:

  • Read references/sector_rotation.md to access market cycle and sector rotation frameworks
  • Compare observed performance patterns against expected patterns for each cycle phase:
    • Early Cycle Recovery
    • Mid Cycle Expansion
    • Late Cycle
    • Recession

Identify which cycle phase best matches current observations by:

  • Mapping outperforming sectors to typical cycle leaders
  • Mapping underperforming sectors to typical cycle laggards
  • Assessing consistency across multiple sectors
  • Evaluating alignment with defensive vs cyclical sector performance
Step 3: Current Situation Analysis

Synthesize observations into an objective assessment:

  • State which market cycle phase current performance most closely resembles
  • Highlight supporting evidence (which sectors/industries confirm this view)
  • Note any contradictory signals or unusual patterns
  • Assess confidence level based on consistency of signals

Use data-driven language and specific references to performance figures.

Step 4: Scenario Development

Based on sector rotation principles and current positioning, develop 2-4 potential scenarios for the next phase:

For each scenario:

  • Describe the market cycle transition
  • Identify which sectors would likely outperform
  • Identify which sectors would likely underperform
  • Specify the catalysts or conditions that would confirm this scenario
  • Assign a probability (see Probability Assessment Framework in sector_rotation.md)

Scenarios should range from most likely (highest probability) to alternative/contrarian scenarios.

Show full SKILL.md (350 more words)Show less
Step 5: Output Generation

Create a structured Markdown document with the following sections:

Required Sections:

  1. Executive Summary: 2-3 sentence overview of key findings
  2. Current Situation: Detailed analysis of current performance patterns and market cycle positioning
  3. Supporting Evidence: Specific sector and industry performance data supporting the cycle assessment
  4. Scenario Analysis: 2-4 scenarios with descriptions and probability assignments
  5. Recommended Positioning: Strategic and tactical positioning recommendations based on scenario probabilities
  6. Key Risks: Notable risks or contradictory signals to monitor

Output Format

Save analysis results as a Markdown file with naming convention: sector_analysis_YYYY-MM-DD.md

Use this structure:

markdown
# Sector Performance Analysis - [Date]

## Executive Summary

[2-3 sentences summarizing key findings]

## Current Situation

### Market Cycle Assessment
[Which cycle phase and why]

### Performance Patterns Observed

#### 1-Week Performance
[Analysis of recent performance]

#### 1-Month Performance
[Analysis of medium-term trends]

#### Sector-Level Analysis
[Detailed breakdown by sector]

#### Industry-Level Analysis
[Notable industry-specific observations]

## Supporting Evidence

### Confirming Signals
- [List data points supporting cycle assessment]

### Contradictory Signals
- [List any conflicting indicators]

## Scenario Analysis

### Scenario 1: [Name] (Probability: XX%)
**Description**: [What happens]
**Outperformers**: [Sectors/industries]
**Underperformers**: [Sectors/industries]
**Catalysts**: [What would confirm this scenario]

### Scenario 2: [Name] (Probability: XX%)
[Repeat structure]

[Additional scenarios as appropriate]

## Recommended Positioning

### Strategic Positioning (Medium-term)
[Sector allocation recommendations]

### Tactical Positioning (Short-term)
[Specific adjustments or opportunities]

## Key Risks and Monitoring Points

[What to watch that could invalidate the analysis]

---
*Analysis Date: [Date]*
*Data Period: [Timeframe of charts analyzed]*

Key Analysis Principles

When conducting analysis:

  1. Objectivity First: Let the data guide conclusions, not preconceptions
  2. Probabilistic Thinking: Express uncertainty through probability ranges
  3. Multiple Timeframes: Compare 1-week and 1-month data for trend confirmation
  4. Relative Performance: Focus on relative strength, not absolute returns
  5. Breadth Matters: Broad-based moves are more significant than isolated movements
  6. No Absolutes: Markets rarely follow textbook patterns exactly
  7. Historical Context: Reference typical rotation patterns but acknowledge uniqueness

Probability Guidelines

Apply these probability ranges based on evidence strength:

  • 70-85%: Strong evidence with multiple confirming signals across sectors and timeframes
  • 50-70%: Moderate evidence with some confirming signals but mixed indicators
  • 30-50%: Weak evidence with limited or conflicting signals
  • 15-30%: Speculative scenario contrary to current indicators but possible

Total probabilities across all scenarios should sum to approximately 100%.

Resources

references/
  • sector_rotation.md - Comprehensive knowledge base covering market cycle phases, typical sector performance patterns, and probability assessment frameworks
assets/

Sample charts demonstrating the expected input format:

  • sector_performance.jpeg - Example sector-level performance chart (1-week and 1-month)
  • industory_performance_1.jpeg - Example industry performance chart (outperformers)
  • industory_performance_2.jpeg - Example industry performance chart (underperformers)

These samples illustrate the type of visual data this skill analyzes. User-provided charts may vary in format but should contain similar relative performance information.

Important Notes

  • All analysis thinking should be conducted in English
  • Output Markdown files must be in English
  • Reference the sector rotation knowledge base for each analysis
  • Maintain objectivity and avoid confirmation bias
  • Update probability assessments if new data becomes available
  • Charts typically show performance over 1-week and 1-month periods

© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references, assets) in workflows/stock-trader-workflow/.claude/skills/sector-analyst of nicepkg/ai-workflow.

  • SKILL.md
  • assets/industory_performance_1.jpeg
  • assets/industory_performance_2.jpeg
  • assets/sector_performance.jpeg
  • references/sector_rotation.md

Open the folder on GitHubat commit d167b41

Compare with similar skills

Sector Analyst 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.

Sector Analyst compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sector Analyst this skillnicepkg/ai-workflow285—~2.1kAutomated safety check: PassMIT
Competitive Cartographercuriositech/some_claude_skills244—~1.3kAutomated safety check: PassMIT
Competitor Intelgooseworks-ai/goose-skills1.2k1 repos~1.8kAutomated safety check: PassMIT
Smr Literature Positioningbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.4kAutomated safety check: PassMIT
List Architectswan-gtm/gtm-skills172—~1.7kAutomated safety check: PassMIT
Marketing OsYuzzyuk/marketing-os540—~2.5kAutomated safety check: PassMIT

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Categories

Questions about Sector Analyst

What does Sector Analyst do?

This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Sector Analyst is an agent skill from nicepkg/ai-workflow. This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns.

When should I use Sector Analyst?

Sector Analyst fits situations like: the user provides performance chart images (1-week; 1-month timeframes) for sectors; industries and requests market cycle assessment; sector rotation analysis.

How do I install Sector Analyst in Claude Code?

Run `npx skills add nicepkg/ai-workflow --skill sector-analyst -a claude-code`. Or copy the skill folder (workflows/stock-trader-workflow/.claude/skills/sector-analyst in nicepkg/ai-workflow) into .claude/skills/sector-analyst in your project. Claude Code loads it when a task matches its description.

How do I install Sector Analyst in Codex?

Run `npx skills add nicepkg/ai-workflow --skill sector-analyst -a codex`. Or copy the skill folder (workflows/stock-trader-workflow/.claude/skills/sector-analyst in nicepkg/ai-workflow) into .agents/skills/sector-analyst in your project. Codex loads it when a task matches its description.

Can I use Sector Analyst 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 nicepkg/ai-workflow --skill sector-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sector-analyst, .gemini/skills/sector-analyst, .github/skills/sector-analyst and .opencode/skills/sector-analyst in your project.

What does Sector Analyst need to run?

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

Does Sector Analyst 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 Sector Analyst 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 Sector Analyst use?

Sector Analyst is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sector Analyst use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Sector Analyst?

Skills that share tags, products or a category with Sector Analyst: Competitive Cartographer (curiositech/some_claude_skills, 244 stars), Competitor Intel (gooseworks-ai/goose-skills, 1.2k stars), Smr Literature Positioning (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars) and List Architect (swan-gtm/gtm-skills, 172 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sector Analyst?

nicepkg (a GitHub organization) maintains it in nicepkg/ai-workflow, which has 285 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on January 20, 2026.

Source: nicepkg/ai-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.