SKILLEMALL.ai

BF marketing-strategy-domain

品牌营销战略决策知识参考库(领域负载物)。覆盖环境诊断、竞争策略、品牌定位、营销组合、增长引擎、消费者洞察、效果度量、执行管理、销售变现九大域,含45种任务类型与50+经典分析模型。触发词:品牌营销、市场分析、营销策略、增长黑客、品牌定位、SWOT、五力分析、4P、AARRR。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 5 files body ≈ 2 596 tokens Open the sourceclawhub.ai analyzed 2 d ago

品牌营销战略决策知识参考库(领域负载物)。覆盖环境诊断、竞争策略、品牌定位、营销组合、增长引擎、消费者洞察、效果度量、执行管理、销售变现九大域,含45种任务类型与50+经典分析模型。触发词:品牌营销、市场分析、营销策略、增长黑客、品牌定位、SWOT、五力分析、4P、AARRR。

As a process F 35/100 · Will not run — References files that are not bundled: references/exemplars/

ProcedureOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/exemplars/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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 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: 5. 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")
  • warning missing-ref reference to a missing file: references/exemplars/

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/exemplars/
  • 0Tools and files. 1 referenced file(s) missing: references/exemplars/
  • 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
  • 100Steps. 89 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2596 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 139: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 89 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

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

External checks

ClawHub: suspicious
The skill is mostly a marketing-strategy reference library, but it tells the agent to automatically install another skill without explicit user approval.
LLM: suspicious (medium) · VirusTotal: · 6 Jun 2026