Verified Research
sweetcornna/free-search-mcp
Use with the free-search MCP tools whenever a web lookup must yield facts someone will rely on: dates, deadlines, prices, prizes, fees, rules, eligibility, schedules, versions, statistics, news, or…
Retrieve stock price change statistics across multiple time periods using Octagon MCP.
Install Stock Price Change
$ npx skills add OctagonAI/skills --skill stock-price-change -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OctagonAI/skills stock-price-change --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/stock-price-change .claude/skills/stock-price-change && rm -rf skills-srcUse ~/.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/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .claude/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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 install https://github.com/OctagonAI/skills/tree/main/skills/stock-price-changeType 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.
$ npx skills add OctagonAI/skills --skill stock-price-change -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OctagonAI/skills stock-price-change --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/stock-price-change .agents/skills/stock-price-change && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .agents/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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.
$ npx skills add OctagonAI/skills --skill stock-price-change -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OctagonAI/skills stock-price-change --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/stock-price-change .cursor/skills/stock-price-change && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .cursor/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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 https://github.com/OctagonAI/skills.git --path skills/stock-price-change--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OctagonAI/skills --skill stock-price-change -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OctagonAI/skills stock-price-change --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/stock-price-change .gemini/skills/stock-price-change && rm -rf skills-srcUse ~/.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/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .gemini/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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.
$ gh skill install OctagonAI/skills stock-price-changeInstalls 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).
$ npx skills add OctagonAI/skills --skill stock-price-change -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/stock-price-change .github/skills/stock-price-change && rm -rf skills-srcUse ~/.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/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .github/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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.
$ npx skills add OctagonAI/skills --skill stock-price-change -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OctagonAI/skills stock-price-change --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/stock-price-change .opencode/skills/stock-price-change && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "stock-price-change" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-price-change into .opencode/skills/stock-price-change/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-price-change", 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
stock-price-change- GitHub stars
- 127
- Token cost
- ~1.7k tokens
- SKILL.md length
- 592 words
- Files
- 5 (incl. references)
- Skills in repo
- 53
- Repo updated
- First seen
- Licence
- MIT
At a glance
Retrieve stock price change statistics across multiple time periods using Octagon MCP.
- Works in 4 steps: Identify the Stock → Execute Query via Octagon MCP → Expected Output → …
- Analyzing short-term and long-term returns
- SKILL.md covers Prerequisites, Workflow, Example Queries and Understanding Time Periods, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Stock Price Change is an agent skill from OctagonAI/skills. Retrieve stock price change statistics across multiple time periods using Octagon MCP. Use when analyzing short-term and long-term returns, comparing performance across timeframes, and evaluating momentum and historical growth.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).
It sits in Data & Analytics, covering Statistics and MCP servers. It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.
When your agent uses it
- Analyzing short-term and long-term returns
- Comparing performance across timeframes
- Evaluating momentum and historical growth
Example prompts
- “/stock-price-change”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 51e938c. 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 json).
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
Stock Price Change loads about 1.7k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 592 words of instructions outside code blocks.
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 OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 592 words, ~1,729 tokens.
Download SKILL.mdSave it as
.claude/skills/stock-price-change/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- stock-price-change
- description
- Retrieve stock price change statistics across multiple time periods using Octagon MCP. Use when analyzing short-term and long-term returns, comparing performance across timeframes, and evaluating momentum and historical growth.
Stock Price Change
Retrieve comprehensive price change statistics across multiple time periods using the Octagon MCP server.
Prerequisites
Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
Workflow
1. Identify the Stock
Determine the ticker symbol for the company you want to analyze (e.g., AAPL, MSFT, GOOGL).
2. Execute Query via Octagon MCP
Use the octagon-agent tool with a natural language prompt:
Get stock price change statistics for the symbol <TICKER>.MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Get stock price change statistics for the symbol AAPL."
}
}3. Expected Output
The agent returns price change data across multiple timeframes:
| Time Period | Percentage Change |
|---|---|
| 1 Day | 4.06% |
| 5 Days | 4.80% |
| 1 Month | -0.37% |
| 3 Months | -0.13% |
| 6 Months | 33.42% |
| Year-to-Date (YTD) | -0.37% |
| 1 Year | 18.42% |
| 3 Years | 79.03% |
| 5 Years | 100.02% |
| 10 Years | 1,043.14% |
| All-Time High | 210,270.08% |
Key Insight: Strong long-term growth with 10-year return of 1,043.14%, but recent short-term performance slightly negative.
Data Sources: octagon-stock-data-agent
4. Interpret Results
See references/interpreting-results.md for guidance on:
- Evaluating short-term vs. long-term performance
- Understanding momentum signals
- Comparing to benchmarks
- Assessing trend consistency
Example Queries
Basic Query:
Get stock price change statistics for the symbol AAPL.Multiple Stocks:
Compare price change statistics for AAPL, MSFT, and GOOGL.Specific Focus:
What is the 1-year and 5-year return for TSLA?YTD Performance:
What is the year-to-date performance of NVDA?Long-Term Growth:
What is the 10-year cumulative return for AMZN?Understanding Time Periods
Short-Term Periods
| Period | Use Case |
|---|---|
| 1 Day | Daily momentum |
| 5 Days | Weekly trend |
| 1 Month | Recent performance |
| 3 Months | Quarterly trend |
Medium-Term Periods
| Period | Use Case |
|---|---|
| 6 Months | Half-year momentum |
| YTD | Calendar year performance |
| 1 Year | Annual return |
Long-Term Periods
| Period | Use Case |
|---|---|
| 3 Years | Business cycle |
| 5 Years | Market cycle |
| 10 Years | Secular trend |
| All-Time | Total return since inception |
Return Interpretation
Performance Classification
| Return (1 Year) | Classification |
|---|---|
| >50% | Exceptional |
| 25-50% | Very strong |
| 10-25% | Strong |
| 0-10% | Moderate |
| -10 to 0% | Weak |
| <-10% | Poor |
Long-Term Standards
| Return (10 Year) | Classification |
|---|---|
| >500% | Exceptional |
| 200-500% | Very strong |
| 100-200% | Strong |
| 50-100% | Moderate |
| 0-50% | Below average |
| <0% | Poor |
Momentum Analysis
Trend Consistency
| Pattern | Interpretation |
|---|---|
| All periods positive | Strong consistent uptrend |
| Short negative, long positive | Pullback in uptrend |
| Short positive, long negative | Bounce in downtrend |
| All periods negative | Consistent downtrend |
Momentum Signals
| Signal | Pattern |
|---|---|
| Accelerating | Returns increasing across periods |
| Decelerating | Returns decreasing across periods |
| Stable | Consistent returns across periods |
| Reversal | Sign change between periods |
Example Analysis
From AAPL data:
- 1 Day: +4.06% (strong daily)
- 1 Month: -0.37% (slight pullback)
- 1 Year: +18.42% (solid annual)
- 10 Year: +1,043.14% (exceptional long-term)
Interpretation: Long-term compounder with recent consolidation.
Show full SKILL.md (223 more words)Show less
Annualized Returns
Calculation
Annualized Return = (1 + Total Return)^(1/Years) - 1Example
From AAPL data:
- 10-Year Return: 1,043.14%
- Annualized: (1 + 10.4314)^(1/10) - 1 = 27.3% per year
Annualized Benchmarks
| Annual Return | Rating |
|---|---|
| >25% | Exceptional |
| 15-25% | Very strong |
| 10-15% | Strong |
| 7-10% | Market-like |
| <7% | Below market |
Comparison Analysis
vs. Benchmarks
| Benchmark | What to Compare |
|---|---|
| S&P 500 | Market performance |
| Sector ETF | Industry performance |
| Peers | Competitive position |
Alpha Calculation
Alpha = Stock Return - Benchmark ReturnExample
If AAPL 1-year return is +18.42% and S&P 500 is +10%:
- Alpha: +8.42% outperformance
Time Period Relationships
Healthy Patterns
| Pattern | Interpretation |
|---|---|
| Long > Short | Healthy uptrend |
| Positive all periods | Consistent strength |
| Improving short-term | Momentum building |
Warning Patterns
| Pattern | Interpretation |
|---|---|
| Long << Short | Mean reversion risk |
| Long > 0, Short < 0 | Trend weakening |
| All negative | Fundamental issues |
All-Time High Analysis
Distance from ATH
Distance = (ATH - Current) / ATH × 100%ATH Context
| Position | Interpretation |
|---|---|
| At ATH | Maximum strength |
| 0-10% below | Near highs |
| 10-20% below | Correction |
| 20-40% below | Bear market |
| >40% below | Severe decline |
Common Use Cases
Performance Summary
What are the returns for AAPL across all time periods?Trend Analysis
Is MSFT in an uptrend or downtrend based on recent returns?Long-Term Growth
What is the 10-year cumulative return for the FAANG stocks?Momentum Check
Is NVDA showing positive momentum in the short-term?Comparison
Compare 1-year returns for major tech stocks.Analysis Tips
Don't rely on one period: Use multiple timeframes.
Compare to benchmarks: Returns mean more in context.
Consider consistency: Smooth vs. volatile returns.
Annualize long-term: For fair comparison.
Watch for divergence: Short vs. long-term signals.
Factor in dividends: Total return vs. price return.
Integration with Other Skills
| Skill | Combined Use |
|---|---|
| stock-quote | Current price context |
| stock-performance | Daily price data |
| stock-historical-index | vs. market returns |
| financial-metrics-analysis | Fundamentals behind returns |
© OctagonAI, 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) in skills/stock-price-change of OctagonAI/skills.
- SKILL.md
- README.md
- marketplace.json
- references/interpreting-results.md
- references/mcp-setup.md
Open the folder on GitHubat commit 51e938c
Compare with similar skills
Stock Price Change 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Stock Price Change this skillOctagonAI/skills | 127 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Verified Researchsweetcornna/free-search-mcp | 126 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Find Hypertable Candidatestimescale/pg-aiguide | 1.9k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Openbb Data Fetchermonarchjuno/vibe-investing | 299 | — | ~2.9k | Automated safety check: Notes | MIT | |
| Odoo Data Quality Gateerpipe-org/mcp-odoo | 421 | — | ~765 | Automated safety check: Pass | MIT | |
| Prod TelemetryUsefulSoftwareCo/executor | 4.1k | — | ~1.9k | Automated safety check: Pass | MIT |
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Questions about Stock Price Change
What does Stock Price Change do?
Retrieve stock price change statistics across multiple time periods using Octagon MCP. Stock Price Change is an agent skill from OctagonAI/skills. Retrieve stock price change statistics across multiple time periods using Octagon MCP.
When should I use Stock Price Change?
Stock Price Change fits situations like: analyzing short-term and long-term returns; comparing performance across timeframes; evaluating momentum and historical growth.
How do I install Stock Price Change in Claude Code?
Run `npx skills add OctagonAI/skills --skill stock-price-change -a claude-code`. Or copy the skill folder (skills/stock-price-change in OctagonAI/skills) into .claude/skills/stock-price-change in your project. Claude Code loads it when a task matches its description.
How do I install Stock Price Change in Codex?
Run `npx skills add OctagonAI/skills --skill stock-price-change -a codex`. Or copy the skill folder (skills/stock-price-change in OctagonAI/skills) into .agents/skills/stock-price-change in your project. Codex loads it when a task matches its description.
Can I use Stock Price Change 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 OctagonAI/skills --skill stock-price-change -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/stock-price-change, .gemini/skills/stock-price-change, .github/skills/stock-price-change and .opencode/skills/stock-price-change in your project.
What does Stock Price Change need to run?
SKILL.md names no scripts, command-line tools or credentials: Stock Price Change is instructions for the agent only.
Does Stock Price Change 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 Stock Price Change 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 Stock Price Change use?
Stock Price Change 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 Stock Price Change use?
About 1.7k tokens (SKILL.md is roughly 6.9k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Stock Price Change?
Skills that share tags, products or a category with Stock Price Change: Verified Research (sweetcornna/free-search-mcp, 126 stars), Find Hypertable Candidates (timescale/pg-aiguide, 1.9k stars), Openbb Data Fetcher (monarchjuno/vibe-investing, 299 stars) and Odoo Data Quality Gate (erpipe-org/mcp-odoo, 421 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Stock Price Change?
OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.
Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.