SKILLEMALL.ai

AB yoooclaw-world-cup-post-match-review-scene-en

Used to generate post-match reviews of World Cup football matches, and supports standardized scene input, post-match information retrieval and fan group notification extraction. It is used when the user needs to summarize the game in one sentence, how the game was played, who played the best, the hot topic after the game, or when the user explicitly requests a full review. The final answer only presents the review content without adding additional paragraphs.

ClawHub Agent Skills author: vivalavida-say-hi v1.0.0 MIT-0 2 files body ≈ 5 009 tokens Open the sourceclawhub.ai analyzed 2 d ago

Used to generate post-match reviews of World Cup football matches, and supports standardized scene input, post-match information retrieval and fan group…

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice

AnalyzerWriting and documentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5009 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 65/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (yoooclaw-world-cup-post-match-review-scene-en) differs from the folder (world-cup-post-match-review-scene-en)
  • 60Steps. 72 steps, 5 vague phrases
  • 70When it triggers. States when to use, but not when not to
  • 70Failures and branches. 9 branches
  • 70Execution cost. Instruction body is 5009 tokens
  • 100Tools and files. No external tools needed
  • 100Result and completion. Output format and completion criterion are stated
  • 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 463: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 72 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
This skill is mostly a football review assistant, but it can query local notifications broadly for fan discussion, so it should be reviewed before installation.
LLM: suspicious (high) · 17 Jul 2026