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AD openclaw-upgrade-assistant

深度分析 OpenClaw 版本更新对现有配置的影响，生成兼容性报告并精准备份受影响文件。Invoke when user asks to analyze OpenClaw updates, check upgrade compatibility, or backup configs before upgrading.

ClawHub Agent Skills author: Adgai115 v1.0.1 MIT-0 80 files body ≈ 1 567 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubSoftware developmentData 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
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
82
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token package-lock.json:43
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…tQV+jkVj…fOB/iy3ssJCD+3KuZ…lAg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:75
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…8CM+MzKM…4lA==",
      detector

    Files scanned: 7. 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 46/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 65 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1567 tokens
    • 100Running it twice. No mutating operations
    • low 15 top-level sections: this looks like several domains in one skill

    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
    • -229 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 160: enough signal without eating the budget
    • +4Structure: 34 headings
    • +3Step-by-step instructions: 65 items
    • +4Has examples (18 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill mostly performs upgrade-impact analysis and workspace report/backup writes, but it asks for exec capability and includes an update-execution example that conflicts with its stated advisory-only boundary.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026