SKILLEMALL.ai
RU Sign in

BD 深知晓

深知晓，为工作场景提供可信安全、精准无幻觉的咨询导办的知识服务，涉及税务社保、法规政策、行业标准；以及申办各类证照、补贴、资质；还有买房购车、养老育儿、上学就业等各种公共服务。深知晓还有分析调研、拟稿写文的能力。以上所有输出内容可逐项索引于动态更新的各权威机构的海量知识网络；并且还可以智能切换任意城市，为你的工作与办事提供可信赖的本地化精准知识服务。

ClawHub Agent Skills author: DKnownAI v1.3.0 MIT-0 9 files body ≈ 3 073 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

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

ProcedureInfrastructuretype 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
84/100
safety, quality, tests
Safety 60%
99
Quality 40%
62
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token scripts/register.mjs:17
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const DEFAULT_GRANT_TOKEN = "Ozqf…uLc";
    quoted

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"

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 (深知晓) differs from the folder (dknowc-know)
  • 100Tools and files. No external tools needed
  • 100Steps. 109 steps
  • 100Execution cost. Instruction body is 3073 tokens
  • 100Running it twice. No mutating operations
  • low 14 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
  • -31 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 176: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 109 items
  • +4Has examples (17 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: clean
This skill is a disclosed public-service Q&A/search integration that uses a remote API and local API-key setup, with credential reuse gated by explicit user confirmation.
LLM: benign (high) · VirusTotal: · 28 Jul 2026