Agent skill

Monitoring Whale Activity

by aAAaqwq in aAAaqwq/AGI-Super-Team

Track large cryptocurrency transactions and whale wallet movements across multiple blockchains.

MITAuto-check passedBusiness, Finance & HR

Install Monitoring Whale Activity

skills CLI
$ npx skills add aAAaqwq/AGI-Super-Team --skill monitoring-whale-activity -a claude-code

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

GitHub CLI
$ gh skill install aAAaqwq/AGI-Super-Team monitoring-whale-activity --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/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/whale-alert-monitor .claude/skills/monitoring-whale-activity && 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
monitoring-whale-activity
GitHub stars
105
Token cost
~945 tokens
SKILL.md length
219 words
Files
12 (incl. scripts, references)
Skills in repo
167
Repo updated
First seen
Licence
MIT

At a glance

Track large cryptocurrency transactions and whale wallet movements across multiple blockchains.

  • Works in 3 steps: Navigate to Scripts Directory → Choose Your Command → Interpret Results
  • Tracking large holder movements
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 3 more sections
  • Runs Python scripts from its folder; calls python

What it does

Monitoring Whale Activity is an agent skill from aAAaqwq/AGI-Super-Team. Track large cryptocurrency transactions and whale wallet movements across multiple blockchains. Monitor exchange inflows/outflows, manage watchlists, Track large cryptocurrency transactions and whale wallet movements in real-time. Use when tracking large holder movements, exchange flows, or wallet activity. Trigger with phrases like "track whales", "monitor large transfers", "check whale activity", "exchange inflows", or "watch wallet".

Its SKILL.md is about 950 tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts and reference files (for example `ARD.md`, `PRD.md` and `config/settings.yaml`).

It sits in Business, Finance & HR, covering Crypto and DeFi analysis. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.

When your agent uses it

  • Tracking large holder movements
  • Wallet activity
  • With phrases like track whales
  • Monitor large transfers

Example prompts

  • “track whales”
  • “monitor large transfers”
  • “check whale activity”
  • “/monitoring-whale-activity”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(python:*whale*)

Workflow steps

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

  1. Navigate to Scripts Directory
  2. Choose Your Command
  3. Interpret Results

What it can do on your machine

Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash(python:*whale*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 5 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • whale-alert.io
    • etherscan.io
    • coingecko.com

    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

Monitoring Whale Activity loads about 945 tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 219 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~945
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 219 words, ~945 tokens.

Download SKILL.mdSave it as .claude/skills/monitoring-whale-activity/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
monitoring-whale-activity
description
Track large cryptocurrency transactions and whale wallet movements across multiple blockchains. Monitor exchange inflows/outflows, manage watchlists, Track large cryptocurrency transactions and whale wallet movements in real-time. Use when tracking large holder movements, exchange flows, or wallet activity. Trigger with phrases like "track whales", "monitor large transfers", "check whale activity", "exchange inflows", or "watch wallet".
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(python:*whale*)
version
1.0.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT

Monitoring Whale Activity

Overview

Track large cryptocurrency transactions and whale wallet movements across multiple blockchains. Monitor exchange inflows/outflows, manage watchlists, and identify known wallets (exchanges, funds, bridges).

Prerequisites

Before using this skill, ensure you have:

  • Python 3.8+ with requests library
  • Whale Alert API key (optional, for live data - free tier available)
  • Internet access for API calls

Instructions

Step 1: Navigate to Scripts Directory
bash
cd {baseDir}/scripts
Step 2: Choose Your Command

Recent Whale Transactions:

bash
python whale_monitor.py recent                    # All chains
python whale_monitor.py recent --chain ethereum   # Specific chain
python whale_monitor.py recent --min-value 10000000  # $10M+ only

Exchange Flow Analysis:

bash
python whale_monitor.py flows                     # Overall exchange flows
python whale_monitor.py flows --chain ethereum    # Chain-specific

Watchlist Management:

bash
python whale_monitor.py watchlist                 # View watchlist
python whale_monitor.py watch 0x123... --name "My Whale"  # Add to watchlist
python whale_monitor.py unwatch 0x123...          # Remove from watchlist

Track Specific Wallet:

bash
python whale_monitor.py track 0x123...            # Track wallet activity

Search Known Labels:

bash
python whale_monitor.py labels --query binance    # Search by name
python whale_monitor.py labels --type exchange    # List by type
Step 3: Interpret Results

Transaction Types:

  • 🔴 DEPOSIT → Exchange (potential selling pressure)
  • 🟢 WITHDRAWAL → From exchange (accumulation signal)
  • 🐋 TRANSFER → Wallet to wallet (whale movement)

Flow Analysis:

  • Net positive flow to exchanges = selling pressure
  • Net negative flow from exchanges = buying pressure

Output

  • Real-time whale transactions with USD values
  • Labeled wallets (exchanges, funds, bridges, protocols)
  • Exchange inflow/outflow summaries
  • Custom watchlist tracking
  • JSON, table, or alert format output

Error Handling

See {baseDir}/references/errors.md for:

  • API rate limit handling
  • Network timeout recovery
  • Invalid address formats
  • Price service fallbacks

Examples

View $10M+ whale transactions on Ethereum:

bash
python whale_monitor.py recent --chain ethereum --min-value 10000000

Analyze if whales are selling (depositing to exchanges):

bash
python whale_monitor.py flows --chain ethereum

Track a known whale wallet:

bash
python whale_monitor.py watch 0x28c6c... --name "Binance Cold"
python whale_monitor.py track 0x28c6c...

Export to JSON for further analysis:

bash
python whale_monitor.py recent --format json > whales.json

See {baseDir}/references/examples.md for more usage patterns.

Resources

  • Whale Alert - Real-time whale transaction API
  • Etherscan - Ethereum blockchain explorer
  • CoinGecko - Price data API
  • Known wallet database with 100+ labeled exchanges and protocols

© aAAaqwq, 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 11 other files (scripts, references) in skills/whale-alert-monitor of aAAaqwq/AGI-Super-Team.

  • SKILL.md
  • ARD.md
  • PRD.md
  • config/settings.yaml
  • references/errors.md
  • references/examples.md
  • references/implementation.md
  • scripts/formatters.py
  • scripts/price_service.py
  • scripts/wallet_labels.py
  • scripts/whale_api.py
  • scripts/whale_monitor.py

Open the folder on GitHubat commit 7cefd81

Compare with similar skills

Monitoring Whale Activity 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.

Monitoring Whale Activity compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Monitoring Whale Activity this skillaAAaqwq/AGI-Super-Team105—~945Automated safety check: PassMIT
Technical Analysttradermonty/claude-trading-skills3k4 repos~4.6kAutomated safety check: PassMIT
Polyclawchainstacklabs/polyclaw3591 repos~2kAutomated safety check: PassApache-2.0
Longbridge Researchhelsome/folio2713 repos~2.1kAutomated safety check: PassMIT
Stock Analysis24mlight/StockClaw1012 repos~2kAutomated safety check: NotesMIT
Swapper Depositswapperfinance/swapper-toolkit852—~1.8kAutomated safety check: PassMIT

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Questions about Monitoring Whale Activity

What does Monitoring Whale Activity do?

Track large cryptocurrency transactions and whale wallet movements across multiple blockchains. Monitoring Whale Activity is an agent skill from aAAaqwq/AGI-Super-Team. Track large cryptocurrency transactions and whale wallet movements across multiple blockchains.

When should I use Monitoring Whale Activity?

Monitoring Whale Activity fits situations like: tracking large holder movements; wallet activity; with phrases like track whales; monitor large transfers.

How do I install Monitoring Whale Activity in Claude Code?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill monitoring-whale-activity -a claude-code`. Or copy the skill folder (skills/whale-alert-monitor in aAAaqwq/AGI-Super-Team) into .claude/skills/monitoring-whale-activity in your project. Claude Code loads it when a task matches its description.

How do I install Monitoring Whale Activity in Codex?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill monitoring-whale-activity -a codex`. Or copy the skill folder (skills/whale-alert-monitor in aAAaqwq/AGI-Super-Team) into .agents/skills/monitoring-whale-activity in your project. Codex loads it when a task matches its description.

Can I use Monitoring Whale Activity 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 aAAaqwq/AGI-Super-Team --skill monitoring-whale-activity -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/monitoring-whale-activity, .gemini/skills/monitoring-whale-activity, .github/skills/monitoring-whale-activity and .opencode/skills/monitoring-whale-activity in your project.

What does Monitoring Whale Activity need to run?

Going by SKILL.md and its folder, Monitoring Whale Activity needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(python:*whale*).

Does Monitoring Whale Activity access the network?

SKILL.md names 3 domains. As links in the text: whale-alert.io, etherscan.io and coingecko.com. This is read from the text; nothing was executed.

Is Monitoring Whale Activity 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Monitoring Whale Activity use?

Monitoring Whale Activity is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Monitoring Whale Activity use?

About 945 tokens (SKILL.md is roughly 3.8k 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 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Monitoring Whale Activity?

Skills that share tags, products or a category with Monitoring Whale Activity: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Polyclaw (chainstacklabs/polyclaw, 359 stars), Longbridge Research (helsome/folio, 271 stars) and Stock Analysis (24mlight/StockClaw, 101 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Monitoring Whale Activity?

aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.

Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.