SKILLEMALL.ai

AC ljh-changjing

场景机会地图。带你把竞品素材拆成能算账的表,用体量乘效率的四象限定性,最后画出自己该重投哪个场景的机会地图。 触发方式:/ljh-changjing、「帮我拆场景」「场景机会地图怎么画」「这几个竞品该怎么对比场景」 Turn competitor content into a scenario opportunity map with a quantified quadrant model. Trigger: /ljh-changjing, "help me map out scenarios", "build a scenario opportunity map" 不要在拆解单条爆款素材因子或评审带货脚本这类环节自动触发。

ClawHub Agent Skills author: HandsoMeng v1.0.0 MIT-0 2 files body ≈ 1 896 tokens Open the sourceclawhub.ai analyzed 2 d ago

场景机会地图。带你把竞品素材拆成能算账的表,用体量乘效率的四象限定性,最后画出自己该重投哪个场景的机会地图。 触发方式:/ljh-changjing、「帮我拆场景」「场景机会地图怎么画」「这几个竞品该怎么对比场景」 Turn competitor content into a scenario…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

Generatortype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
53/100
Has gaps
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

    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

    • note frontmatter-key unknown frontmatter key "slug"

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1896 tokens
    • 100Running it twice. No mutating operations
    • low 11 top-level sections: this looks like several domains in one skill

    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 2 example trigger phrases
    • +3Description length 316: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    The skill is mainly a business analysis helper, but it automatically creates local state and can persist commercially sensitive brand files with limited user control.
    LLM: suspicious (high) · 6 Aug 2026