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BD ragflow-kb

RAGFlow知识库问答与操作指导。调用RAGFlow知识库API进行智能问答，并基于知识库返回结果提供agent操作建议。支持流式输出，耐心等待完整响应生成。当用户提出技术问题、故障排查、操作指导或需要知识库检索时触发此技能。适用于容器/Docker问题、系统运维、开发相关问题等场景。

ClawHub Agent Skills author: chenkun-nuaa v1.0.0 6 files · 1 script body ≈ 845 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceDockerInfrastructuretype 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
85/100
safety, quality, tests
Safety 60%
98
Quality 40%
65
Run on models
none yet
Process rating
D
49/100
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Obfuscation obf-base64-blob scripts/query_ragflow.py:23
    Long base64-looking blob (quoted — discussed, not commanded)
    COOKIE = "session=.elx…siB/MyNq…xp4"
    quoted
  • low Obfuscation obf-base64-blob scripts/quick_test.py:15
    Long base64-looking blob (test fixture / example file; quoted — discussed, not commanded)
    COOKIE = "session=.elx…siB/MyNq…xp4"
    fixturequoted

Files scanned: 6. 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 49/100

  • 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
  • 40Consistency. Frontmatter name (ragflow-kb) differs from the folder (ck-rag-skill)
  • 100Tools and files. No external tools needed
  • 100Steps. 52 steps
  • 100Execution cost. Instruction body is 845 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)
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 144: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 52 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
The skill appears to do the advertised RAGFlow Q&A job, but it ships reusable API credentials and shared conversation state that users should review before installing.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026