SKILLEMALL.ai

CD admapix

Ad intelligence & app analytics assistant. Search ad creatives, analyze apps, view rankings, track downloads/revenue, and get market insights via api.admapix.com. Triggers: 找素材, 搜广告, 广告素材, 竞品分析, 广告分析, 排行榜, 下载量, 收入分析, 市场分析, 投放分析, App分析, 出海分析, search ads, find creatives, ad spy, ad analysis, app ranking, download data, revenue, market analysis, app intelligence, competitor analysis, ad distribution.

The same skill from clawhub has been run on models: No improvement D see the result → This is a copy: its text may differ, so the grade is not carried over.

ClawHub Agent Skills author: GodferyLindsay v1.0.0 MIT-0 11 files body ≈ 2 719 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Ad intelligence & app analytics assistant.

As a process D 47/100 · Unfinished process — References files that are not bundled: url

IntegrationData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
D
47/100
Unfinished process
References files that are not bundled: url
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: admapix (ClawHub)

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

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Map keys must be unique at line 3, column 1: name: admapix name: admapix ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (admapix) differs from the folder (martin-admapix)
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 46 steps, 2 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 100Execution cost. Instruction body is 2719 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 400: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 46 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: clean
This is a coherent AdMapix analytics skill whose main risks are expected third-party API sharing, API-key handling, and one unpinned install example, not hidden malicious behavior.
LLM: benign (high) · VirusTotal: benign · 16 Sept 2026