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BD 深知晓办公助手

深知晓办公助手，是由北京彩智科技有限公司旗下“深知可信智能”提供的综合办公助手，统一覆盖公文写作、可信咨询、可信检索、PPT 生成四大类办公场景，并可持续扩展更多能力。可用于公文与正式材料起草（通知、请示、报告、函、会议纪要、总结、方案、讲话稿、调研报告等文种的起草、改写、润色、压缩、审查和 Word/红头交付）、政策法规与政务办事咨询（税务社保、公积金、企业补贴、资质证照、行业标准、合规义务、办理条件、材料清单、申请路径、风险判断，输出带真实来源角标和可点击溯源 HTML 的答案）、权威材料检索与核验（政策依据查找、政策调研、城市政策对比、补贴税惠材料核验、深度搜索、政策可视化）、以及原生可编辑 PPT 生成（工作汇报、专题汇报、政策宣讲、培训课件，从需求直接生成或从已有材料提炼，5 种党政合规风格 + 8 种画布规格，约束 SVG → 原生 DrawingML 编译导出真实 PowerPoint）。所有事实素材都通过深知可信智能的权威文件库检索，全程可溯源。

ClawHub Agent Skills author: Dylan Zhang v1.1.0 MIT-0 80 files body ≈ 2 390 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

IntegrationPowerPointWordSoftware developmentAI 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%
100
Quality 40%
64
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

The same skill appears in 1 more place: ClawHub

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: 80. 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 "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note frontmatter-key unknown frontmatter key "secrets"

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
  • 40Consistency. Frontmatter name (深知晓办公助手) differs from the folder (dknowc-office-assistant)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 33 steps
  • 100Execution cost. Instruction body is 2390 tokens
  • 100Running it twice. No mutating operations
  • low 11 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 437: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is a disclosed office-assistant skill that sends user queries and an API key to the provider’s service and writes local document outputs, with no confirmed malicious behavior.
LLM: benign (medium) · VirusTotal: · 3 Sept 2026