Agent skill

Stock Grades

Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP.

MITAuto-check passed

Install Stock Grades

skills CLI

$ npx skills add OctagonAI/skills --skill stock-grades -a claude-code

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

GitHub CLI

$ gh skill install OctagonAI/skills stock-grades --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/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/stock-grades .claude/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .claude/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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/OctagonAI/skills/tree/main/skills/stock-grades

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 OctagonAI/skills --skill stock-grades -a codex

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

GitHub CLI

$ gh skill install OctagonAI/skills stock-grades --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/stock-grades .agents/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .agents/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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 OctagonAI/skills --skill stock-grades -a cursor

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

GitHub CLI

$ gh skill install OctagonAI/skills stock-grades --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/stock-grades .cursor/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .cursor/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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/OctagonAI/skills.git --path skills/stock-grades

--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 OctagonAI/skills --skill stock-grades -a gemini-cli

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

GitHub CLI

$ gh skill install OctagonAI/skills stock-grades --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/OctagonAI/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/stock-grades .gemini/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .gemini/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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 OctagonAI/skills stock-grades

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 OctagonAI/skills --skill stock-grades -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/stock-grades .github/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .github/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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 OctagonAI/skills --skill stock-grades -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 OctagonAI/skills stock-grades --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/stock-grades .opencode/skills/stock-grades && 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 "stock-grades" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/stock-grades into .opencode/skills/stock-grades/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "stock-grades", 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-grades
GitHub stars: 127
Token cost: ~1.7k tokens
SKILL.md length: 557 words
Files: 5 (incl. references)
Skills in repo: 53
Repo updated: Jun 5, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP.

Works in 4 steps: Identify the Stock → Execute Query via Octagon MCP → Expected Output → …
Tracking analyst upgrades
SKILL.md covers Prerequisites, Workflow, Example Queries and Understanding Rating Scales, plus 6 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Stock Grades is an agent skill from OctagonAI/skills. Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP. Use when tracking analyst upgrades, downgrades, rating changes, and institutional sentiment 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

Tracking analyst upgrades
Institutional sentiment over time

Example prompts

“/stock-grades”

Workflow steps

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

Identify the Stock
Execute Query via Octagon MCP
Expected Output
Interpret Results

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 Grades loads about 1.7k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 56 tokens; SKILL.md has 557 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~56
When it runs · the whole SKILL.md, loaded when a task matches: ~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~4k

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). 557 words, ~1,671 tokens.

Download SKILL.mdSave it as .claude/skills/stock-grades/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.

name: stock-grades
description: Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP. Use when tracking analyst upgrades, downgrades, rating changes, and institutional sentiment over time.

Stock Grades

Retrieve analyst grades, ratings, and rating changes from top financial institutions 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 the latest stock grades for the symbol <TICKER> from top analysts and financial institutions.

MCP Call Format:

json

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Get the latest stock grades for the symbol AAPL from top analysts and financial institutions."
  }
}

3. Expected Output

The agent returns analyst rating history including:

Rating Actions: Upgrades, downgrades, maintains
Analyst/Institution: Source of the rating
Previous Rating: Prior grade
New Rating: Current grade
Date: When the rating was issued

Example: Maxim Group upgraded from Hold to Buy on 2026-01-30

Data Sources: octagon-stock-data-agent

4. Interpret Results

See references/interpreting-results.md for guidance on:

Understanding rating scales
Analyzing upgrade/downgrade trends
Evaluating analyst credibility
Tracking sentiment changes

Example Queries

Basic Query:

Get the latest stock grades for the symbol AAPL from top analysts and financial institutions.

Recent Changes:

What are the most recent analyst rating changes for TSLA?

Upgrade Focus:

Show me recent upgrades for NVDA from major investment banks.

Historical View:

What is the history of analyst ratings for MSFT over the past year?

Specific Institution:

What is Goldman Sachs' current rating on AMZN?

Understanding Rating Scales

Common Rating Systems

Rating Level	Common Terms
Strong Buy	Buy, Overweight, Outperform
Buy	Accumulate, Add, Positive
Hold	Neutral, Market Perform, Equal-Weight
Sell	Underweight, Underperform, Reduce
Strong Sell	Sell, Avoid

Rating Equivalencies

Bank A	Bank B	Bank C	Meaning
Overweight	Buy	Outperform	Bullish
Equal-Weight	Hold	Market Perform	Neutral
Underweight	Sell	Underperform	Bearish

Rating Actions

Action Types

Action	Description
Upgrade	Rating improved (e.g., Hold → Buy)
Downgrade	Rating lowered (e.g., Buy → Hold)
Maintain	Rating unchanged (reaffirmed)
Initiate	New coverage started
Reiterate	Rating repeated with emphasis
Resume	Coverage restarted
Suspend	Coverage temporarily halted

Significance Ranking

Action	Impact
Upgrade from Sell	Highest positive
Upgrade from Hold	Significant positive
Initiate at Buy	Positive
Maintain at Buy	Stable positive
Downgrade to Hold	Negative signal
Downgrade to Sell	Highest negative

Analyst Credibility

Factors to Consider

Factor	Description
Track Record	Historical accuracy
Institution Tier	Major bank vs. boutique
Sector Expertise	Specialization
Coverage Length	Experience with stock
Independence	Conflicts of interest

Institution Tiers

Tier	Examples
Bulge Bracket	Goldman Sachs, Morgan Stanley, JPMorgan
Major Banks	Bank of America, Citi, UBS
Boutiques	Wedbush, Piper Sandler, Needham
Independent	Morningstar, CFRA

Show full SKILL.md (222 more words)Show less

Trend Analysis

Sentiment Indicators

Pattern	Interpretation
Multiple upgrades	Improving sentiment
Multiple downgrades	Deteriorating outlook
Mixed actions	Uncertainty/debate
All maintains	Stable consensus

Momentum Signals

Signal	Meaning
Upgrade cluster	Catalyst or breakout
Downgrade cluster	Concerns emerging
Initiation wave	Growing interest
Coverage drops	Reduced attention

Rating Distribution

Consensus Rating

Distribution	Interpretation
Mostly Buy	Strong bullish consensus
Mostly Hold	Neutral/wait-and-see
Mostly Sell	Bearish consensus
Mixed	Divergent views

Rating Counts

Metric	What It Shows
Buy %	Bullish proportion
Hold %	Neutral proportion
Sell %	Bearish proportion
Total Analysts	Coverage level

Timing Considerations

When Ratings Change

Catalyst	Typical Timing
Earnings	Day of or day after
Guidance	Within 24-48 hours
Product News	Same day
Macro Events	As needed
Sector Rotation	Periodic

Staleness

Age	Reliability
<1 month	Current view
1-3 months	Reasonably current
3-6 months	May be outdated
>6 months	Likely stale

Common Use Cases

Sentiment Check

What is the current analyst sentiment on AAPL?

Change Monitoring

Have any analysts upgraded or downgraded TSLA recently?

Catalyst Research

Why did analysts upgrade NVDA last week?

Consensus View

What percentage of analysts rate MSFT as a buy?

Historical Tracking

How has analyst sentiment on META changed over the past year?

Analysis Tips

Weight by institution: Major banks carry more weight.
Track changes, not just ratings: Upgrades/downgrades signal shifts.
Consider timing: Post-earnings ratings are most current.
Look for clusters: Multiple changes = significant.
Check track record: Some analysts are more accurate.
Combine with targets: Rating + price target = complete view.

Integration with Other Skills

Skill	Combined Use
price-target-consensus	Ratings + price targets
analyst-estimates	Ratings + earnings expectations
stock-quote	Rating changes + price reaction
stock-performance	Historical ratings vs. performance

Files

SKILL.md and 4 other files (references) in skills/stock-grades 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 Grades 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.

Stock Grades compared with similar skills
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MCP Integration for Pluginsanthropics/claude-plugins-official	38k	11 repos	~3.1k	Automated safety check: Pass	Apache-2.0	today
MCP Developmentcoollabsio/coolify	63k	1 repos	~949	Automated safety check: Pass	MIT	yesterday
Analyze Logsactivepieces/activepieces	25k	1 repos	~1.6k	Automated safety check: Pass	MIT	today

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Questions about Stock Grades

What does Stock Grades do?

Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP. Stock Grades is an agent skill from OctagonAI/skills. Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP.

When should I use Stock Grades?

Stock Grades fits situations like: tracking analyst upgrades; institutional sentiment over time.

How do I install Stock Grades in Claude Code?

Run `npx skills add OctagonAI/skills --skill stock-grades -a claude-code`. Or copy the skill folder (skills/stock-grades in OctagonAI/skills) into .claude/skills/stock-grades in your project. Claude Code loads it when a task matches its description.

How do I install Stock Grades in Codex?

Run `npx skills add OctagonAI/skills --skill stock-grades -a codex`. Or copy the skill folder (skills/stock-grades in OctagonAI/skills) into .agents/skills/stock-grades in your project. Codex loads it when a task matches its description.

Can I use Stock Grades 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-grades -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-grades, .gemini/skills/stock-grades, .github/skills/stock-grades and .opencode/skills/stock-grades in your project.

What does Stock Grades need to run?

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

Does Stock Grades 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 Grades 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 Grades use?

Stock Grades 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 Grades 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 Stock Grades?

Skills that share tags, products or a category with Stock Grades: 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 Stock Grades?

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.

Install Stock Grades

Facts

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

Credentials

Context cost

Safety

SKILL.md

Stock Grades

Prerequisites

Workflow

1. Identify the Stock

2. Execute Query via Octagon MCP

3. Expected Output

4. Interpret Results

Example Queries

Understanding Rating Scales

Common Rating Systems

Rating Equivalencies

Rating Actions

Action Types

Significance Ranking

Analyst Credibility

Factors to Consider

Institution Tiers

Trend Analysis

Sentiment Indicators

Momentum Signals

Rating Distribution

Consensus Rating

Rating Counts

Timing Considerations

When Ratings Change

Staleness

Common Use Cases

Sentiment Check

Change Monitoring

Catalyst Research

Consensus View

Historical Tracking

Analysis Tips

Integration with Other Skills

Files

Compare with similar skills

Similar skills

More from OctagonAI/skills

Related

Questions about Stock Grades