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AB solana-meme-analyzer

Analyze Solana meme token (CA) risk by scanning holder distribution, detecting insider wallets (老鼠仓/rat warehouse), and evaluating top-holder concentration. Use when the user wants to analyze a Solana token contract address, check for rugs, detect insiders, evaluate meme coin safety, check holder concentration, or assess if a token is likely to be dumped. Keywords: CA分析, 老鼠仓, 控盘, 持仓分析, Solana token risk.

ClawHub Agent Skills author: Lougseus v1.0.1 16 files body ≈ 1 102 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: consistency, progress reporting

AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
97
Quality 40%
90
Run on models
none yet
Process rating
B
69/100
Nearly there
Progress reporting w 2
0
Consistency w 8
40
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Secrets in code secret-high-entropy-token api/server.py:59
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "asset": "0x83…913",  # USDC on Base
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:145
      High-entropy token-like string (may be an id, hash or a credential)
      python3 {baseDir}/scripts/psdm.py EPjF…t1v
    • low Secrets in code secret-high-entropy-token SKILL.md:151
      High-entropy token-like string (may be an id, hash or a credential)
      python3 {baseDir}/scripts/psdm.py EPjF…t1v --json

    Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (solana-meme-analyzer) differs from the folder (memeanalyzer)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 11 steps
    • 100Execution cost. Instruction body is 1102 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 407: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 11 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    The analyzer’s core token-risk functionality is coherent, but its agent-facing paid crypto payment path needs careful review before installation.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026