SKILLEMALL.ai

BD 深知公文写作

深知公文写作,是面向单位办公室、综合岗、文秘、材料岗和企事业单位用户的正式材料写作助手。核心用于公文写作、正式文书起草、汇报材料整理、讲话稿撰写、工作总结和方案报告生成,帮助用户把零散想法、会议记录、工作素材、调研资料或初稿,整理成结构清楚、表达稳妥、逻辑完整、可直接修改使用的正式文稿。支持通知、请示、报告、函、复函、批复、会议纪要、通报、通告、公告、意见、方案、总结、管理办法、汇报材料、发言稿、讲话稿、调研报告、经验材料等常见文种和工作材料。可进行起草、改写、润色、扩写、压缩、标题优化、结构调整、语气统一和内容审查。涉及政策依据、数据支撑、标准规范或案例参考时,可调用深知可信搜索获取素材,并单独生成可信核验报告,帮助用户写得有依据、能复核、可交付。正式交付时支持生成 Word 文档;用户明确需要时,也可生成红头文件。

ClawHub Agent Skills author: DKnownAI v3.5.0 MIT-0 65 files body ≈ 5 612 tokens Open the sourceclawhub.ai analyzed 5 d ago

As a process D 40/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
D
40/100
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 65. 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")
  • warning body-long SKILL.md body ≈ 5612 tokens (recommended < 5000); move details to references/
  • 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 40/100

  • 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 (深知公文写作) differs from the folder (dknownai-official-doc-writer)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5612 tokens
  • 100Steps. 151 steps
  • 100Running it twice. No mutating operations
  • low 12 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
  • -33 of 14 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 364: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 151 items
  • +4Has examples (19 code blocks)
  • +4Reference files are cited in the instructions (11 of 11)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: suspicious
The skill has a real document-writing purpose, but it needs Review because it handles phone verification, account/API-key provisioning, persistent shell-profile secrets, full secret output, and automatic file delivery.
LLM: suspicious (high) · 2 Sept 2026