SKILLEMALL.ai
GitHub ↗ RU Sign in

BC ruankao-essay-writing

覆盖软考高级论文写作全流程，支持全部 5 个高级资格（系统架构设计师/信息系统项目管理师/系统分析师/网络规划设计师/系统规划与管理师）。提供项目准备、试题分析、提纲撰写、摘要撰写、正文填充、检查校对全流程指导，按用户资格类型选择对应的项目案例、写作视角和专业深度标准。当用户提到"帮我写论文""论文指导""如何准备论文""改论文""论文提纲""论文模板"等涉及论文写作的需求时触发。不适用于论文评分（那是 ruankao-essay-scoring 的职责）。

ClawHub Agent Skills author: Nieen v1.2.3 MIT-0 14 files body ≈ 2 314 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

覆盖软考高级论文写作全流程，支持全部 5…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorWriting and documentstype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
53/100
Has gaps
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 · 0

✓ No critical or high findings

Files scanned: 14. 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")
  • note frontmatter-key unknown frontmatter key "related_skills"
  • note frontmatter-key unknown frontmatter key "created"
  • note frontmatter-key unknown frontmatter key "skill_type"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 74 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2314 tokens
  • 100Running it twice. No mutating operations
  • 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 231: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 74 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (12 of 12)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a document-only exam essay writing helper whose read/write permissions fit drafting and editing user-provided essays.
LLM: benign (high) · VirusTotal: · 23 Aug 2026