SKILLEMALL.ai

BB max-global-pathway

Bilingual global undergraduate pathway advisor for international high schools, bilingual schools and pathway programmes. Provides source-aware, non-agent-like guidance across UK, US, Australia, New Zealand, Hong Kong, Macau, Singapore, Malaysia, Thailand, Korea, Japan and related destinations.

ClawHub Agent Skills author: Max Liu v3.1.0 MIT-0 8 files body ≈ 10 908 tokens Open the sourceclawhub.ai analyzed 27 h ago

Bilingual global undergraduate pathway advisor for international high schools, bilingual schools and pathway programmes.

As a process B 67/100 · Nearly there — weak spots: result and completion, consistency, execution cost

ProcedureInfrastructureData and analyticsResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
B
67/100
Nearly there
Progress reporting w 2
0
Result and completion w 14
40
Consistency w 8
40
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 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: 8. 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 body-long SKILL.md body ≈ 10908 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "emoji"

Process rating: all ten parameters 67/100

  • 0Progress reporting. Says nothing while it works
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (max-global-pathway) differs from the folder (goglobal-adcotemax)
  • 40Execution cost. Instruction body is 10908 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 460 steps
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 53 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

  • +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 294: enough signal without eating the budget
  • +4Structure: 103 headings
  • +3Step-by-step instructions: 460 items
  • +4Has examples (6 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is a disclosed education-advising skill with minor marketing/contact notes but no hidden execution, credential access, persistence, or unsafe data handling.
LLM: benign (high) · VirusTotal: · 21 Jun 2026