crypto-analyze

crypto-analyze is a skill for Claude Code, Codex from zubair-trabzada/ai-crypto-claude. It costs 27 tokens per session (4,339 once invoked), scanned A, original, MIT.

A cryptocurrency research workflow that gathers token data, asks five analysis agents to examine it from different angles, and combines their findings into one report with a score from 0 to 100.

In plain words
What is it for?
Use it to investigate a cryptocurrency using its ticker, name, contract address, or CoinGecko identifier, then review a combined analysis.
Why use it?
It removes the need to collect and compare several types of token information by hand. It is for research only, not financial advice.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to investigate a cryptocurrency using its ticker, name, contract address, or CoinGecko identifier, then review a combined analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zubair-trabzada/ai-crypto-claude/crypto-analyze
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zubair-trabzada/ai-crypto-claude --skill crypto-analyze
Clone the repo
git clone --depth 1 https://github.com/zubair-trabzada/ai-crypto-claude

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for crypto-analyze

README.md
[![agentmods](https://agentmods.dev/badge/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze/github.svg)](https://agentmods.dev/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze)
Your own site
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for crypto-analyze

Your own site · 80×15
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-crypto-claude/crypto-analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,339 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.04339
Opus 5 $0.00014 $0.02169
Sonnet 5 $0.00005 $0.00868
Haiku 4.5 $0.00003 $0.00434

Measured 12d ago against content hash 0775c9dbcbbb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

crypto-analyze scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/crypto-analyze/SKILL.md · 464 lines

How it starts

The opening of the file, as written. The whole thing — 464 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Full Crypto Analysis Orchestrator

You are the flagship crypto analysis orchestrator for the AI Crypto Analyst system. When invoked with /crypto analyze <token>, you perform a comprehensive, multi-dimensional analysis of any cryptocurrency token by launching 5 parallel subagents and synthesizing their findings into a unified research report with a composite Crypto Score (0-100).

DISCLAIMER: For educational/research purposes only. Not financial advice. Cryptocurrency is highly volatile. Always DYOR.


EXECUTION PIPELINE

Follow these three phases exactly. Do not skip or reorder phases.

PHASE 1: DISCOVERY (You do this directly — do NOT delegate)

Before launching any agents, gather foundational data yourself using WebSearch.

Step 1 — Identify the Token

Parse the user input. Accept any of:

  • Ticker symbol: BTC, ETH, SOL, ARB
  • Full name: Bitcoin, Ethereum, Solana, Arbitrum
  • Contract address: 0x... (resolve to token name/ticker)
  • CoinGecko slug: bitcoin, ethereum, solana

Normalize to: TOKEN_TICKER (uppercase), TOKEN_NAME (proper case), COINGECKO_SLUG (lowercase-hyphenated).

Step 2 — Baseline Data Retrieval

Run WebSearch queries to establish the token profile:

WebSearch: "[TOKEN_NAME] [TOKEN_TICKER] current price market cap 24h volume 2026"
WebSearch: "[TOKEN_NAME] crypto category chain ecosystem overview"
WebSearch: "[TOKEN_NAME] token unlock schedule vesting 2026"

Extract and record:

  • Current price (USD)
  • Market capitalization
  • Fully diluted valuation (FDV)
  • 24-hour trading volume
  • 24h / 7d / 30d / 90d price change %
  • Circulating supply vs max supply
  • Chain / Layer (Ethereum, Solana, its own L1, etc.)
  • Category classification (see below)
  • CoinGecko / CoinMarketCap rank

Step 3 — Category Detection

Classify the token into one of these categories to tailor agent prompts:

Category Examples Focus Areas
Layer 1 BTC, ETH, SOL, AVAX, SUI Network activity, validator economics, ecosystem growth, developer activity
Layer 2 ARB, OP, STRK, MATIC, BASE TVL growth, tx volume, sequencer revenue, bridge flows, L1 settlement costs
DeFi UNI, AAVE, MKR, CRV, PENDLE TVL, protocol revenue, fee generation, governance, capital efficiency
AI / DePIN TAO, RNDR, FIL, HNT, AKT Network utilization, real demand metrics, token burn/earn mechanics
Meme DOGE, SHIB, PEPE, WIF, BONK Social momentum, whale concentration, liquidity depth, holder distribution
RWA ONDO, MAPLE, CENTRIFUGE Real asset backing, regulatory status, institutional adoption
Gaming / Metaverse IMX, GALA, AXS, ILV Player count, in-game economy, NFT volume, studio partnerships
Infrastructure LINK, GRT, PYTH, API3 Integration count, data request volume, fee revenue, enterprise adoption
Privacy XMR, ZEC, SCRT Transaction volume, regulatory risk, adoption metrics
Stablecoin USDT, USDC, DAI, FRAX Peg stability, reserves composition, regulatory risk, market share trend

Read the full file on GitHub · 464 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 464 lines · 27 tokens per session scan A 0775c9dbcbbb

Subscribe to this mod's changes

crypto-analyze is a skill published in the GitHub repository zubair-trabzada/ai-crypto-claude (48 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 4,339 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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