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BD openclaw-config-backuper

Backup OpenClaw config files, Skills, Workspace files, and Memory records for migration or disaster recovery. 备份 OpenClaw 配置文件、技能、工作区文件和记忆记录，用于迁移或灾难恢复。Triggers: 备份, backup, 备份配置, backup config, 配置备份, config backup, 备份OpenClaw, backup openclaw, 迁移配置, migrate config, 恢复配置, restore config, 导出配置, export config, 配置迁移, config migration, 灾难恢复, disaster recovery, 备份技能, backup skills, 备份工作区, backup workspace, 备份记忆, backup memory, OpenClaw备份, openclaw backup, 配置导出, config export, 系统备份, system backup, 配置文件备份, config files backup.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files · 1 script body ≈ 328 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Backup OpenClaw config files, Skills, Workspace files, and Memory records for migration or disaster recovery.

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsAI 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
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
41/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 0

✓ No critical or high findings

Files scanned: 2. 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")

Process rating: all ten parameters 41/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 85Steps. 9 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 328 tokens
  • high The skill tells the model to perform an irreversible action with no human approval

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 524: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 9 items
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.