SKILLEMALL.ai

AD fore-vip-product-recommend

通用产品调研与推荐框架(fore.vip)。把模糊的「帮我推荐个产品 / 该买哪个 / 选型对比 / 适合我的 X / 测评对比 / 选型清单 / 帮我选」转化为有依据、可溯源、分层的结构化推荐。覆盖全行业全品类,暂不涉及 CPS 选品。标准流程:① 需求澄清(使用者/诉求/约束/优先级)② 构建评估维度并赋权(必选四维:需求匹配·性能质量·TCO·风险合规;可选:口碑·售后·易用·扩展)③ 多渠道调研采集(竞品清单/评测/社区/官方,标注来源·时间·适用范围)④ 加权评分矩阵横向对比 ⑤ 结构化产出(首选/备选/避坑 + 事实依据 + 来源 + 行动建议)。遵循 fore.vip 核心准则:先结论后依据、事实/分析/建议三级分离、数据可溯源。当用户请求产品推荐、测评对比、选型决策、采购清单时使用。

ClawHub Agent Skills author: Fore.vip v1.0.1 MIT-0 4 files body ≈ 443 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

ReferenceInfrastructuretype 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: 4. 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 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 (fore-vip-product-recommend) differs from the folder (fore-vip-product)
  • 100Tools and files. No external tools needed
  • 100Steps. 23 steps
  • 100Execution cost. Instruction body is 443 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 354: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: clean
This is a product-recommendation workflow skill with broad triggers, but it does not request execution authority, credentials, persistence, or destructive capabilities.
LLM: benign (high) · VirusTotal: · 18 Aug 2026