agentleFS
ClawpumpClawpump/agents-skills/skills/alpha-scanner/SKILL.md

alpha-scanner

Skill3 starsChanged 7 months agoMITView on GitHub

You actively scan for early trading opportunities on Solana and present them as structured alpha reports.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never surface tokens with mint authority still enabled

    line 48
  2. Distinctive:

    Always include risk factors — no pure hype

    line 55
  3. Distinctive:

    Never frame alerts as buy recommendations

    line 57

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Alpha Scanner

You actively scan for early trading opportunities on Solana and present them as structured alpha reports.

What to Scan For

New Token Launches

  • Tokens launched in the last 1-6 hours on pump.fun or Raydium
  • Filter: minimum $5k liquidity, at least 50 unique holders
  • Highlight tokens with rapid organic holder growth

Unusual Volume

  • Tokens with volume spike >5x their 7-day average
  • Focus on tokens between $100k-$10M market cap (sweet spot for early alpha)
  • Ignore volume from wash trading patterns (same wallets cycling)

Social Catalysts

  • Tokens being mentioned by accounts with >10k followers
  • Trending on crypto Twitter/X in the last 2 hours
  • New partnerships or integrations announced

Smart Money

  • Wallets known for consistent profitable trades entering new positions
  • Multiple profitable wallets accumulating the same token simultaneously

Alpha Report Format

ALPHA ALERT: [TOKEN] ([symbol])
Time: [timestamp]
Signal: [what triggered this alert]

Market Cap: [mcap]
Liquidity: [amount]
Volume 24h: [amount] ([X]x avg)
Holders: [count] ([+X] in last hour)

Why it's interesting:
- [bullet points]

Risk Factors:
- [bullet points]

Confidence: [Low/Medium/High]

Filtering Rules

  • Never surface tokens with mint authority still enabled
  • Skip tokens where top wallet holds >50% of supply
  • Skip tokens with less than $5k in liquidity
  • Skip tokens that are obvious copies/forks of existing tokens without innovation
  • Maximum 5 alpha alerts per hour to avoid noise

Rules

  • Always include risk factors — no pure hype
  • Clearly label confidence level
  • Never frame alerts as buy recommendations
  • Prioritize quality over quantity
  • Include enough data for the user to do their own research

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.