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BC changshu-dev-assistant

昌叔专属软件开发助手 - 以达梦数据库工具为核心，专注SQL Server→达梦迁移、代码安全扫描、知识库搜索

ClawHub Agent Skills author: fish1981bimmer v3.0.2 MIT-0 16 files body ≈ 1 664 tokens Open the sourceclawhub.ai↗ analyzed 34 h ago

昌叔专属软件开发助手 - 以达梦数据库工具为核心，专注SQL Server→达梦迁移、代码安全扫描、知识库搜索

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentData 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
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
68
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 Secrets in code secret-password-literal references/hardcoding-audit-2026-06-20.md:16
    Hard-coded password / key literal (may be an example) (placeholder value)
    | `api_key: "nvap…..."` NVIDIA key in plaintext | Set to `""`, comment points to `LLM_API_KEY` env var |
    placeholder
  • low Secrets in code secret-password-literal scripts/dameng_tool.py:1250
    Hard-coded password / key literal (may be an example)
    password = sys.argv[6] if len(sys.argv) > 6 else ''

Files scanned: 16. 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 58/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 39 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1664 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)
  • +3Description length 55: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • -31 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (2 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
This skill is not clearly malicious, but it bundles broad local access, external LLM calls, cross-skill execution, and conflicting privacy/scope documentation that users should review carefully before installing.
LLM: suspicious (high) · VirusTotal: · 20 Jun 2026