SKILLEMALL.ai

AC marketing-strategy

Chinese marketing strategy planner with API-powered benchmarks (中文数字营销策略规划+平台基准数据API). Create data-driven marketing plans for 小红书/抖音/微信/百度/电商 with real platform benchmarks via API. Features: (1) API-powered platform benchmarks (avg views, completion rates, budget splits), (2) Audience analysis, content calendar, budget allocation, KPI framework, (3) Executable benchmarks.sh script for CLI access, (4) Covers organic growth + paid advertising strategies, (5) 2026 industry benchmarks. Use when: marketing strategy, Chinese marketing, 小红书策略, 抖音运营, 营销计划, budget allocation, KPI framework, digital marketing China. Triggers: marketing strategy, Chinese marketing, 小红书策略, 抖音运营, 营销计划, budget allocation, KPI framework, digital marketing China, marketing benchmarks, platform KPIs, 营销基准, 平台数据, marketing API, benchmarks API.

ClawHub Agent Skills author: lm203688 v1.0.0 MIT-0 3 files · 1 script body ≈ 1 200 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

IntegrationData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 59/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 74 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1200 tokens

    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)
    • +3Description length 820: 120–800 characters recommended
    • +1No license
    • +2Single-language instructions
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 74 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is a coherent China-focused marketing strategy skill with a disclosed benchmark API helper and no evidence of hidden, destructive, or credential-seeking behavior.
    LLM: benign (high) · VirusTotal: · 28 May 2026