SKILLEMALL.ai

AD competitor-analyzer

使用场景: - 用户说"竞品分析"、"做竞调" - 用户说"帮我分析XX和XX" - 用户说"竞争对手有哪些" - 用户说"产品对比"、"市场调研" - 用户粘贴竞品名称说"帮我做个分析" - 用户说"了解XX行业" - 用户说"做个对比报告" 不适用: - 股票分析(用stock-research-group) - 行业深度报告(用research-company) - 个人职业规划(用career-advisor) - 纯闲聊

ClawHub Agent Skills author: miromiraclemiro-ux v2.0.0 MIT-0 2 files body ≈ 1 140 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
D
49/100
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 · 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 description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 49/100

  • 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 (competitor-analyzer) differs from the folder (sutang-competitor-analyzer)
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 57 steps
  • 100Execution cost. Instruction body is 1140 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

  • +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
  • +5Description quotes 6 example trigger phrases
  • +3Description length 217: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 57 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a coherent competitor-analysis prompt with proportionate web research and report-writing behavior, but users should avoid sharing confidential strategy if they do not want it reused as context.
LLM: benign (high) · VirusTotal: · 29 May 2026