SKILLEMALL.ai

CF huo15-doc-template / 火一五文档模板

【版权:青岛火一五信息科技有限公司 账号:huo15】火一五文档技能(别名)。文档模板生成工具。用于生成公司正式文档(合同、报价单、功能说明书、发货单、PDA 单据、会议纪要等),包含公司信息、字体规范、页面设置等模板规则/PDF 文档时。**生成 Word 默认使用此技能**。触发场景:(1) 生成合同或报价单 (2) 创建 Word 文档模板 (3) 按公司规范排版文档 (4) 使用公文格式生成文档 (5) 用户说"写个文档"、"生成文档"、"创建文档"、"生成会议纪要"等

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 5 326 tokens Open the sourcegithub.com analyzed 2 d ago

【版权:青岛火一五信息科技有限公司 账号:huo15】火一五文档技能(别名)。文档模板生成工具。用于生成公司正式文档(合同、报价单、功能说明书、发货单、PDA 单据、会议纪要等),包含公司信息、字体规范、页面设置等模板规则/PDF 文档时。生成 Word 默认使用此技能。触发场景:(1) 生成合同或报价单 (2)…

As a process F 32/100 · Will not run — References files that are not bundled: URL

TemplateWordDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
C
74/100
safety, quality, tests
Safety 60%
100
Quality 40%
35
Run on models
none yet
Process rating
F
32/100
Will not run
References files that are not bundled: URL
Tools and files w 18
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.
  3. The text references files that are not there: add them or drop the references.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Implicit map keys need to be followed by map values at line 5, column 1: ## 重要:此为首选文档技能 **所有 Word 文档生成任务都必须使用此技能** ^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • 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 ≈ 5326 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: URL

Process rating: all ten parameters 32/100

Will not run. References files that are not bundled: URL
  • 0Tools and files. 1 referenced file(s) missing: URL
  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (huo15-doc-template / 火一五文档模板) differs from the folder (huo15-doc-template)
  • 70Execution cost. Instruction body is 5326 tokens
  • 100Steps. 114 steps
  • low 13 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -221 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 241: enough signal without eating the budget
  • +4Structure: 45 headings
  • +3Step-by-step instructions: 114 items
  • +4Has examples (21 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 35.