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BC cl-lp-rebalancer

Uniswap V3 集中流动性 LP 自动调仓策略。基于波动率自适应范围宽度：低波动率收紧范围（高资本效率），高波动率放宽范围（减少调仓和 IL）。支持趋势不对称调整、多时间框架分析、自动 claim/remove/swap/deposit 全流程。适用于 EVM L2 链上 CL LP 管理、调仓、范围优化、手续费最大化场景。用户查询收益、PnL、仓位、头寸状态、LP 状况、年化、手续费、无常损失时，调用 status 子命令即可获取（每 5 分钟缓存一次，秒级响应）。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 12 files · 1 script body ≈ 5 471 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Uniswap V3 集中流动性 LP 自动调仓策略。基于波动率自适应范围宽度：低波动率收紧范围（高资本效率），高波动率放宽范围（减少调仓和 IL）。支持趋势不对称调整、多时间框架分析、自动 claim/remove/swap/deposit 全流程。适用于 EVM L2 链上 CL LP…

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ProcedureInfrastructureData 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
B
78/100
safety, quality, tests
Safety 60%
91
Quality 40%
59
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 9

✓ No critical or high findings

Medium and low: 9
  • low Dangerous commands cmd-cron-mention INTRODUCTION.md:271
    Mentions editing / listing crontab
    crontab -e
  • low Exfiltration read-dotenv README.md:67
    Reads a .env file
    cp ../.env.example .env    # 填入 API keys + 钱包地址
  • low Exfiltration exfil-webhook-url references/cl_lp.py:2168
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendMessage"
    placeholder
  • low Secrets in code secret-high-entropy-token references/cli-reference.md:73
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "address": "0x83…913",
    quoted
  • low Secrets in code secret-high-entropy-token references/cli-reference.md:367
    High-entropy token-like string (may be an id, hash or a credential)
    --to 0x83…913 \
  • low Secrets in code secret-high-entropy-token references/cli-reference.md:400
    High-entropy token-like string (may be an id, hash or a credential)
    --to 0x83…913 \
  • low Secrets in code secret-high-entropy-token references/cli-reference.md:433
    High-entropy token-like string (may be an id, hash or a credential)
    --token 0x83…913 \
  • low Secrets in code secret-high-entropy-token references/cli-reference.md:487
    High-entropy token-like string (may be an id, hash or a credential)
    --to 0x83…913 \
  • low Secrets in code secret-high-entropy-token SKILL.md:466
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "token1": "0x83…913",
    quoted

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5471 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5471 tokens
  • 85Steps. 99 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (26 tags): a typed call is more reliable

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
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +3Description length 239: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 99 items
  • +4Has examples (13 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.