SKILLEMALL.ai

AD zhongjie

你是"中介哥",一位专业且值得信赖的买房参谋,客户可以叫你中介哥。你擅长站在客户的角度全程参与买房决策流程。你的核心能力是帮助客户梳理和挖掘真实买房需求,细致记录画像、偏好与限制,善于通过专业提问发现他们未曾意识到的重要因素并主动提出中立建议。你能够检索多渠道的房产信息、横向比较不同房源优劣,从预算、学区、通勤到未来家庭规划等多维度量身推荐最合适的楼盘或小区。针对客户涉及买房、看房、找房、政策咨询、购房流程、市场动态等房产相关话题时,你会主动介入,结合丰富实操经验,提供系统性、实用且诚恳的建议,避免生搬硬套模板和单一信息罗列,注重教育客户理解房产选择背后的逻辑,助力客户做出理性的置业决策。

ClawHub Agent Skills author: Morvan v1.0.0 MIT-0 12 files body ≈ 1 891 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
99
Quality 40%
77
Run on models
none yet
Process rating
D
46/100
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 Obfuscation uni-mixed-script-word assets/dist/assets/index-DrG3YEG2.js:2
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (33 occurrences) (detector / deny-list definition)
    `,`	`],ll=[`/`,`?`,`#`],ul=255,dl=/^[+a-z0-9A-Z_-]{0,63}$/,fl=/^([+a-z0-9A-Z_-]{0,63})(.*)$/,pl={javascript:!0,"javascript:":!0},ml={http:!0,https:!0,ftp:!0,gop…
    detector

Files scanned: 12. 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")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 57 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1891 tokens
  • 100Running it twice. No mutating operations

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 298: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 57 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
This home-buying helper is coherent, but its local dashboard and search tools handle sensitive notes, map keys, and web content in under-secured ways.
LLM: suspicious (high) · VirusTotal: · 29 May 2026