ct-alpha

CT Alpha — Crypto Twitter Intelligence

Turn X/Twitter into an actionable crypto intelligence layer. Search CT for narratives, alpha, strategies, and sentiment, then rank results using TweetRank (a PageRank-inspired credibility scoring system), extract tokens/CAs from multiple signals, detect coordinated raids, and suggest execution steps using available tools.

Overview

Search: Query CT with crypto-optimized noise filters and relevancy sorting
TweetRank: Score tweets by author credibility + engagement quality + recency
Multi-Signal Token Detection: Cashtags, name-phrases, crypto URLs, contract addresses
Raid Detection: Flag tickers promoted mostly by low-credibility accounts
Trending: Detect trending tokens across multiple search queries
Watchlist: Monitor trusted CT accounts by category
Thread Hydration: Fetch full conversation threads
X Articles: Full-text extraction of long-form posts (>280 chars)
Cost Tracking: Per-session API spend tracking (~$0.005/tweet)
Dynamic Tool Discovery: Suggest follow-up actions with DeFi Llama, Backpack, Polymarket, etc.

Prerequisites

Runtime: Bun (TypeScript runtime)
API Token: X API Bearer Token from developer.x.com (pay-per-use via xAI)
Cost: ~$0.005 per tweet read, ~$0.10 per quick search (20 tweets)

Quick Start

Installation

# Clone the skill
git clone https://github.com/yashhsm/skills.git
cd skills/skills/ct-alpha

# Run the installer (configures token, watchlist, cache)
bun run install.ts

Environment Setup

# Set your X API Bearer Token
export X_BEARER_TOKEN="your_token_here"

# Or save to persistent env file
mkdir -p ~/.config/env
echo 'export X_BEARER_TOKEN="your_token_here"' >> ~/.config/env/global.env
source ~/.config/env/global.env

Basic Usage

# Search for alpha on a token
bun run ct-search.ts search "$SOL alpha" --quick

# Detect trending tokens
bun run ct-search.ts trending --window 6h --solana-only

# Monitor watchlist accounts
bun run ct-search.ts watchlist --since 24h

# Read a specific tweet or article
bun run ct-search.ts read https://x.com/user/status/123456

# Check API spending
bun run ct-search.ts cost

CLI Reference

search — Core research command

bun run ct-search.ts search "<query>" [flags]

Flag	Description	Default
`--quick`	20 tweets, 1hr cache, ~$0.10	Default mode
`--full`	Up to 100 tweets, 15min cache, ~$0.50	Confirm cost first
`--limit N`	Max total tweets	20 (quick), 100 (full)
`--sort <field>`	`likes`, `recency`, `relevancy`	`relevancy`
`--since <duration>`	`1h`, `6h`, `24h`, `7d`	`24h`
`--min-likes N`	Engagement filter	3 (quick)
`--from user1,user2`	Restrict to specific accounts	—
`--extract-tickers`	Show extracted tickers	—
`--extract-cas`	Show contract addresses and crypto URLs	—
`--raw`	JSON output	—

bun run ct-search.ts trending [flags]

Flag	Description	Default
`--window <duration>`	`1h`, `6h`, `24h`	`6h`
`--min-mentions N`	Minimum mention count	3
`--solana-only`	Solana ecosystem only	—
`--top N`	Top N results	20

watchlist — Monitor CT accounts

bun run ct-search.ts watchlist [flags]

Flag	Description	Default
`--category <cat>`	Filter by category	all
`--since <duration>`	Time window	`24h`

read — Read a specific tweet/article

bun run ct-search.ts read <tweet_url_or_id> [--thread] [--raw]

Accepts x.com URLs, twitter.com URLs, or raw tweet IDs. Articles (long-form posts) are fetched in full.

thread — Hydrate conversation thread

bun run ct-search.ts thread <tweet_id>

cost — Track API spending

bun run ct-search.ts cost [--reset]

Core Features

TweetRank Scoring

Every tweet is scored by three factors multiplied together:

AuthorCred (0-10): Watchlist membership (+5), follower/following ratio (capped +5), verification (+1), account age (log scale, capped +2), bot penalty (-3)
EngagementQuality: Bookmarks (×3, unfakeable) > Quotes (×2.5, high effort) > Likes (×1.5) > Retweets (×1, easily botted). All log-scaled.
RecencyBoost: 1 / (1 + hoursAgo / 24) — newer tweets score higher.

TweetRank = AuthorCred × EngagementQuality × RecencyBoost

Each tweet receives a source label:

[WATCHLIST] — Author is on your watchlist (highest trust)
[HIGH-CRED] — AuthorCred ≥ 5
[UNKNOWN] — Unverified author
[SUSPICIOUS] — Bot-like patterns detected

Multi-Signal Token Detection

Cashtag-only detection misses how tokens actually spread on CT. This extracts from four signal types:

Signal	Example	Confidence
Cashtag	`$SOL`, `$JTO`	High
Name-phrase	“pendle” + crypto context	High/Medium
Crypto URL	pump.fun, dexscreener, birdeye, jup.ag	High
Contract Address	Base58 (Solana) / 0x (Ethereum) with context	High/Low

Supported crypto URL domains: pump.fun, dexscreener.com, birdeye.so, jup.ag, raydium.io, solscan.io, etherscan.io.

Raid Detection

Detects coordinated pump campaigns by analyzing author credibility distribution per ticker:

If >70% of authors mentioning a ticker have low credibility (AuthorCred < 3), it’s flagged as a potential raid
Output includes raid score, total/low-cred author counts

Noise Filtering

Every search auto-appends crypto noise filters:

-is:retweet (removes retweets)
-"airdrop", -"giveaway", -"whitelist" (spam removal)
-"follow and RT", -"follow & RT", -"free mint", -"dm to claim" (engagement bait)
Quick mode also adds -is:reply

Caching

Aggressive caching prevents redundant API calls:

Cache Type	TTL	Use Case
Quick search	1 hour	Default searches
Full search	15 minutes	Deep dives
Thread	2 hours	Conversation threads
Profile	24 hours	User lookups
Watchlist	4 hours	Account monitoring

Cache is file-based (JSON) with auto-pruning on startup (24h hard limit).

Research Methodology

Follow this 6-step loop for every research request:

1. Decompose

Break the user’s question into 1-3 targeted search queries.

Token research: search both $TICKER and plain name with OR
Narratives: search thematic keywords, not just token names
Strategies: include strategy/yield/APY keywords

2. Pre-Filter

Before any API call:

Check cache (same query within TTL is free)
Noise filters are automatic
Estimate cost: Quick ~$0.10, Full ~$0.50-1.50
Narrow time window: 24h for trending, 7d for research

3. Search

Execute with --quick mode first (always):

bun run ct-search.ts search "$TOKEN alpha" --quick --extract-tickers

4. Extract

Analyze TweetRank scores and trust labels. Look for extracted tickers, contract addresses, and crypto URLs.

5. Deep-Dive (if needed)

Follow high-engagement threads: bun run ct-search.ts thread <id>
Search specific authors: --from author1,author2
Broaden with --full only if quick was insufficient

6. Synthesize

Combine findings into actionable intelligence:

Group by theme, not by query
Highlight tickers with strong multi-signal detection
Flag raid risks
Suggest verification and execution steps

Query String Rules

The query argument supports X API v2 operators:

Operator	Example	Description
keyword	`solana alpha`	Both words
`"exact"`	`"yield strategy"`	Exact phrase
`OR`	`$SOL OR solana`	Either term
`-`	`-airdrop`	Exclude term
`from:`	`from:username`	Tweets by user
`has:links`	`has:links`	Tweets with URLs
`lang:`	`lang:en`	Language filter
`$`	`$SOL`	Cashtag

Do NOT use these v1.1 operators (they cause 400 errors on v2 pay-per-use):

min_faves:N, min_retweets:N — use --min-likes CLI flag instead
place:, bio:, sample: — not available on v2

Do NOT manually include noise filters in the query — the CLI auto-appends them.

Dynamic Tool Discovery

After completing research, suggest execution steps using available MCP tools:

Tool Prefix	Use Case	Example
`mcp__defillama__*`	TVL, yields, fees, prices	`get_protocol_tvl("pendle")`
`mcp__backpack__*`	Exchange price, depth, trades	`backpack_get_ticker("SOL_USDC")`
`mcp__polymarket__*`	Prediction markets	`search_polymarket("solana ETF")`
`mcp__coingecko__*`	Token data, market charts	`get_id_coins("solana")`

Always frame suggestions as “verify” not “confirm” — encourage skepticism about CT alpha.

Cost Protocol

Always --quick first (~$0.10 for 20 tweets). Relevancy sort = best results come first.
Only increase --limit if 20 results are genuinely insufficient.
Display cost estimate before --full mode.
Cache is aggressive — same query within TTL is free.
Two-pass strategy: First search 20 results. If more depth needed on a sub-topic, do a targeted follow-up rather than re-running with higher limits.

Best Practices

Start narrow, broaden only if needed: Specific ticker + context words first
Use --from for signal: Restrict to watchlist accounts for highest signal-to-noise
Use has:links for substance: Analytical content, not hot takes
Never present CT findings as authoritative: Always include confidence levels and risk bullets
Contract addresses are always UNVERIFIED: Verify on-chain before interacting
Two-pass research: Quick search first, then targeted deep-dives
Track spending: Use cost command to monitor API usage

Security Considerations

X Bearer Token is stored in ~/.config/env/global.env — ensure proper file permissions
Never commit tokens to version control
Contract addresses extracted from tweets are ALWAYS unverified — always verify on-chain
Watchlist data is local-only (not synced or shared)
Cache files contain tweet data — consider cleanup for sensitive research

Skill Structure

ct-alpha/
├── SKILL.md                    # This file — agent instructions
├── ct-search.ts                # Main CLI entry point
├── setup.ts                    # Interactive setup script
├── install.ts                  # Full installer
├── lib/
│   ├── api.ts                  # X API v2 integration, pagination, caching
│   ├── extract.ts              # Multi-signal token extraction
│   ├── tweetrank.ts            # TweetRank scoring and raid detection
│   ├── format.ts               # Output formatting with trust labels
│   ├── cache.ts                # File-based caching layer
│   ├── cost.ts                 # API cost tracking
│   └── filters.ts              # Noise filtering, engagement filtering
├── resources/
│   ├── x-api.md                # X API v2 reference
│   ├── query-templates.md      # Pre-built search patterns
│   └── tool-discovery.md       # Dynamic tool suggestion map
├── data/
│   ├── known-tokens.json       # Token name → ticker mappings
│   └── watchlist.default.json  # Default watchlist categories
└── examples/
    └── basic-search.ts         # Quick start example

Skill contents

CT Alpha — Crypto Twitter Intelligence

Overview

Prerequisites

Quick Start

Installation

Environment Setup

Basic Usage

CLI Reference

search — Core research command

watchlist — Monitor CT accounts

read — Read a specific tweet/article

thread — Hydrate conversation thread

cost — Track API spending

Core Features

TweetRank Scoring

Multi-Signal Token Detection

Raid Detection

Noise Filtering

Caching

Research Methodology

1. Decompose

2. Pre-Filter

3. Search

4. Extract

5. Deep-Dive (if needed)

6. Synthesize

Query String Rules

Dynamic Tool Discovery

Cost Protocol

Best Practices

Security Considerations

Skill Structure

Resources

ct-alpha

Skill contents

CT Alpha — Crypto Twitter Intelligence

Overview

Prerequisites

Quick Start

Installation

Environment Setup

Basic Usage

CLI Reference

search — Core research command

trending — Multi-signal trending detection

watchlist — Monitor CT accounts

read — Read a specific tweet/article

thread — Hydrate conversation thread

cost — Track API spending

Core Features

TweetRank Scoring

Multi-Signal Token Detection

Raid Detection

Noise Filtering

Caching

Research Methodology

1. Decompose

2. Pre-Filter

3. Search

4. Extract

5. Deep-Dive (if needed)

6. Synthesize

Query String Rules

Dynamic Tool Discovery

Cost Protocol

Best Practices

Security Considerations

Skill Structure

Resources