AF algorithm-learning-platform-builder
build interactive algorithm learning pages, comparison pages, and reusable teaching platforms for algorithms. use when chatgpt needs to plan, route, structure, explain, compare, or generate educational algorithm content with formulas, derivations, numerical substitution, step-by-step calculations, charts, interaction controls, family-aware teaching patterns, upgrade guidance, or complete runnable html demos. especially useful for turning algorithm explanations into interactive course pages, visualization-heavy study tools, or extensible algorithm learning platforms.
As a process F 53/100 · Will not run — References files that are not bundled: references/output-quality-checklist.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/output-quality-checklist.md
Process rating: all ten parameters 53/100
- 0Tools and files. 1 referenced file(s) missing: references/output-quality-checklist.md
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (algorithm-learning-platform-builder) differs from the folder (skills-of-algorithm-learning-platform-builder)
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 10 branches
- 100Steps. 151 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 2246 tokens
- low 15 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 572: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 151 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (9 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.