MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Retrieve analysts' price target summary for any stock using Octagon MCP.
MITAuto-check passed
Install Price Target Summary
$ npx skills add OctagonAI/skills --skill price-target-summary -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OctagonAI/skills price-target-summary --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/price-target-summary .claude/skills/price-target-summary && 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 "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .claude/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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/price-target-summaryType 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 price-target-summary -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OctagonAI/skills price-target-summary --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/price-target-summary .agents/skills/price-target-summary && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .agents/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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 price-target-summary -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OctagonAI/skills price-target-summary --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/price-target-summary .cursor/skills/price-target-summary && 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 "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .cursor/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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/price-target-summary--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 price-target-summary -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OctagonAI/skills price-target-summary --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/price-target-summary .gemini/skills/price-target-summary && 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 "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .gemini/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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 price-target-summaryInstalls 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 price-target-summary -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/price-target-summary .github/skills/price-target-summary && 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 "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .github/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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 price-target-summary -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 price-target-summary --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/price-target-summary .opencode/skills/price-target-summary && 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 "price-target-summary" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/price-target-summary into .opencode/skills/price-target-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "price-target-summary", 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
price-target-summary- GitHub stars
- 127
- Token cost
- ~1.7k tokens
- SKILL.md length
- 544 words
- Files
- 5 (incl. references)
- Skills in repo
- 53
- Repo updated
- First seen
- Licence
- MIT
At a glance
Retrieve analysts' price target summary for any stock using Octagon MCP.
- Works in 4 steps: Identify the Stock → Execute Query via Octagon MCP → Expected Output → …
- Evaluating analyst sentiment
- SKILL.md covers Prerequisites, Workflow, Example Queries and Understanding Price Targets, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Price Target Summary is an agent skill from OctagonAI/skills. Retrieve analysts' price target summary for any stock using Octagon MCP. Use when evaluating analyst sentiment, upside/downside potential, consensus expectations, and tracking target trends over time.
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 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
- Evaluating analyst sentiment
- Upside/downside potential
- Consensus expectations
- Tracking target trends over time
Example prompts
- “/price-target-summary”
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
Price Target Summary loads about 1.7k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 55 tokens; SKILL.md has 544 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). 544 words, ~1,687 tokens.
Download SKILL.mdSave it as
.claude/skills/price-target-summary/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- price-target-summary
- description
- Retrieve analysts' price target summary for any stock using Octagon MCP. Use when evaluating analyst sentiment, upside/downside potential, consensus expectations, and tracking target trends over time.
Price Target Summary
Retrieve aggregated analyst price target data across multiple timeframes 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:
Retrieve the analysts' price-target summary for the stock symbol <TICKER>.MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Retrieve the analysts' price-target summary for the stock symbol AAPL."
}
}3. Expected Output
The agent returns price target data across timeframes:
| Timeframe | Number of Analysts | Average Price Target |
|---|---|---|
| Last Month | 9 | $305.72 |
| Last Quarter | 16 | $312.80 |
| Last Year | 48 | $282.91 |
| All Time | 229 | $219.71 |
Key Insights: Trend analysis comparing timeframes
Data Sources: octagon-stock-data-agent (aggregating StreetInsider, TheFly, Benzinga, etc.)
4. Interpret Results
See references/interpreting-results.md for guidance on:
- Analyzing target trends
- Calculating upside/downside potential
- Understanding analyst coverage
- Evaluating consensus strength
Example Queries
Basic Query:
Retrieve the analysts' price-target summary for the stock symbol AAPL.With Current Price Context:
What are the analyst price targets for TSLA compared to its current price?Trend Focus:
How have analyst price targets for NVDA changed over the past year?Coverage Analysis:
How many analysts cover Microsoft and what are their price targets?Range Request:
What are the highest and lowest analyst price targets for AMZN?Understanding Price Targets
What Price Targets Represent
| Aspect | Description |
|---|---|
| Definition | Analyst's expected stock price |
| Timeframe | Typically 12 months forward |
| Basis | Fundamental and technical analysis |
| Purpose | Guide for fair value |
Types of Price Targets
| Type | Description |
|---|---|
| Average | Mean of all targets |
| Median | Middle value |
| High | Most bullish target |
| Low | Most bearish target |
| Consensus | Weighted average |
Timeframe Analysis
Understanding Timeframes
| Timeframe | What It Shows |
|---|---|
| Last Month | Most recent sentiment |
| Last Quarter | Near-term trend |
| Last Year | Annual evolution |
| All Time | Historical context |
Trend Interpretation
| Pattern | Interpretation |
|---|---|
| Rising targets | Growing optimism |
| Falling targets | Increasing concern |
| Stable targets | Consensus maintained |
| Diverging targets | Uncertainty/debate |
Calculating Potential
Upside/Downside
Upside = (Target Price - Current Price) / Current Price × 100%Example Calculation
- Current Price: $270.01
- Average Target: $312.80
- Upside: ($312.80 - $270.01) / $270.01 = 15.8%
Interpreting Potential
| Upside | Interpretation |
|---|---|
| >20% | Significant upside expected |
| 10-20% | Moderate upside |
| 0-10% | Near fair value |
| <0% | Downside risk |
Analyst Coverage
Coverage Levels
| Analysts | Coverage Level |
|---|---|
| 30+ | Heavily covered |
| 15-30 | Well covered |
| 5-15 | Moderate coverage |
| <5 | Limited coverage |
Coverage Implications
| Level | Characteristics |
|---|---|
| Heavy | More consensus reliability |
| Moderate | Good perspective diversity |
| Light | Less reliable consensus |
| Minimal | Limited institutional interest |
Show full SKILL.md (216 more words)Show less
Consensus Strength
Evaluating Consensus
| Factor | Strong Consensus | Weak Consensus |
|---|---|---|
| Range | Tight (low to high) | Wide spread |
| Recent Changes | Aligned direction | Mixed revisions |
| Analyst Count | Many participants | Few analysts |
Standard Deviation
| Spread | Interpretation |
|---|---|
| Narrow | High agreement |
| Moderate | Normal debate |
| Wide | Significant disagreement |
Target Revisions
Revision Trends
| Pattern | Signal |
|---|---|
| Upgrades increasing | Improving outlook |
| Downgrades increasing | Deteriorating outlook |
| Mixed revisions | Uncertainty |
| No changes | Status quo |
Revision Triggers
| Catalyst | Common Result |
|---|---|
| Strong earnings | Target increases |
| Weak earnings | Target decreases |
| Guidance change | Aligned revision |
| Sector news | Coordinated moves |
Data Sources
Common Publishers
| Source | Description |
|---|---|
| StreetInsider | Financial news aggregator |
| TheFly | Real-time news |
| Benzinga | Market intelligence |
| Sell-side Firms | Investment bank research |
Source Considerations
| Factor | Note |
|---|---|
| Timeliness | Recent targets more relevant |
| Reputation | Weight by analyst track record |
| Conflicts | Consider investment banking ties |
| Methodology | Different valuation approaches |
Common Use Cases
Investment Decision
Should I buy AAPL based on analyst targets?Valuation Check
Is MSFT overvalued relative to analyst expectations?Sentiment Tracking
How has analyst sentiment on GOOGL changed this year?Peer Comparison
Compare analyst targets for major cloud stocks.Analysis Tips
Compare to current price: Calculate upside/downside potential.
Track trend direction: Rising or falling targets over time.
Consider coverage: More analysts = more reliable consensus.
Check range: Tight = agreement, wide = uncertainty.
Time weight: Recent targets more relevant.
Use with fundamentals: Targets are opinions, not facts.
Integration with Other Skills
| Skill | Combined Use |
|---|---|
| stock-quote | Current price vs. target |
| analyst-estimates | Targets + earnings expectations |
| income-statement | Fundamentals behind targets |
| stock-performance | Price trend vs. target evolution |
© 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/price-target-summary 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
Price Target Summary 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 |
|---|---|---|---|---|---|---|
| Price Target Summary this skillOctagonAI/skills | 127 | — | ~1.7k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| MCP Developmentcoollabsio/coolify | 63k | 1 repos | ~949 | Automated safety check: Pass | MIT | |
| Analyze Logsactivepieces/activepieces | 25k | 1 repos | ~1.6k | Automated safety check: Pass | MIT |
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Questions about Price Target Summary
What does Price Target Summary do?
Retrieve analysts' price target summary for any stock using Octagon MCP. Price Target Summary is an agent skill from OctagonAI/skills. Retrieve analysts' price target summary for any stock using Octagon MCP.
When should I use Price Target Summary?
Price Target Summary fits situations like: evaluating analyst sentiment; upside/downside potential; consensus expectations; tracking target trends over time.
How do I install Price Target Summary in Claude Code?
Run `npx skills add OctagonAI/skills --skill price-target-summary -a claude-code`. Or copy the skill folder (skills/price-target-summary in OctagonAI/skills) into .claude/skills/price-target-summary in your project. Claude Code loads it when a task matches its description.
How do I install Price Target Summary in Codex?
Run `npx skills add OctagonAI/skills --skill price-target-summary -a codex`. Or copy the skill folder (skills/price-target-summary in OctagonAI/skills) into .agents/skills/price-target-summary in your project. Codex loads it when a task matches its description.
Can I use Price Target Summary 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 price-target-summary -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/price-target-summary, .gemini/skills/price-target-summary, .github/skills/price-target-summary and .opencode/skills/price-target-summary in your project.
What does Price Target Summary need to run?
SKILL.md names no scripts, command-line tools or credentials: Price Target Summary is instructions for the agent only.
Does Price Target Summary 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 Price Target Summary 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 Price Target Summary use?
Price Target Summary 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 Price Target Summary use?
About 1.7k tokens (SKILL.md is roughly 6.7k 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 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Price Target Summary?
Skills that share tags, products or a category with Price Target Summary: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and MCP Development (coollabsio/coolify, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Price Target Summary?
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.