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AC solana-sniper-bot

Autonomous Solana token sniper and trading bot. Monitors new token launches on Raydium/Jupiter, evaluates rugpull risk with LLM analysis, auto-buys promising launches, and manages exit strategies. Use when user wants to snipe Solana token launches, trade memecoins, monitor new Solana pairs, or build a Solana trading bot. Supports cron-based monitoring, take-profit/stop-loss, and portfolio tracking.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files · 1 script body ≈ 785 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Autonomous Solana token sniper and trading bot.

As a process C 62/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice

AnalyzerInfrastructureAI and agentstype 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
93/100
safety, quality, tests
Safety 60%
95
Quality 40%
91
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token references/jupiter-api.md:23
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - SOL: `So11…112`
      quoted
    • low Secrets in code secret-high-entropy-token references/jupiter-api.md:24
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - USDC: `EPjF…t1v`
      quoted
    • low Secrets in code secret-high-entropy-token references/jupiter-api.md:25
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - USDT: `Es9v…NYB`
      quoted
    • low Secrets in code secret-high-entropy-token scripts/sniper.py:27
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      SOL_MINT = "So11…112"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/sniper.py:28
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_MINT = "EPjF…t1v"
      quoted

    Files scanned: 5. 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 62/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 785 tokens

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 401: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 28 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.