SKILLEMALL.ai

BB Learn

Runs self-directed learning as a system: a curriculum with an exit test, deliberate practice, spaced review, and proof it transferred. Use when someone is teaching themselves a skill or subject with no course and no exam — a language, an instrument, a programming language, a new field at work; when they ask how to learn X, what to learn first, or how long it will honestly take; when months of tutorials produced nothing they can build; when material learned earlier is gone, reviews pile up, or the queue gets skipped for weeks; when progress stalls on a plateau, motivation collapses, or a skill goes rusty after a lapse; when practice feels productive but nothing transfers to real work; when an AI answers so fast that nothing is being learned at all; and when a plan, review schedule, error log, or mastery record has to survive across sessions. Not for teaching a concept in the moment (`learning`), exam and coursework planning (`studying`), or authoring decks (`anki`, `flashcards`).

ClawHub Agent Skills author: Iván v1.0.4 MIT-0 17 files body ≈ 6 017 tokens Open the sourceclawhub.ai analyzed 36 h ago

Runs self-directed learning as a system: a curriculum with an exit test, deliberate practice, spaced review, and proof it transferred.

As a process B 75/100 · Nearly there — weak spots: inputs and preconditions, running it twice

ProcedureLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
B
75/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
the three weakest of ten parameters · all ten

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 6017 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 75/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 12 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 70Execution cost. Instruction body is 6017 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 42 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • +3Description length 993: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 42 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This learning skill is mostly coherent, but it asks to automatically read and change persistent local learning, contact, project, and finance records, including deletions or subscription cancellation steps, without enough user confirmation.
LLM: suspicious (high) · VirusTotal: · 10 Sept 2026