BB curriculum-generator
Intelligent educational curriculum generation system with strict step enforcement and human escalation policies
As a process B 79/100 · Nearly there — weak spots: execution cost
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 10516 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 79/100
- 40Execution cost. Instruction body is 10516 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 10 branches
- 100Steps. 228 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 20 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)
- +3Description length 111: 120–800 characters recommended
- -5TODO / placeholder text left in the skill
- -232 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 73 headings
- +3Step-by-step instructions: 228 items
- +3Output format is stated explicitly
- +4Has examples (49 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.
External checks
ClawHub: suspicious
The skill has a legitimate curriculum-generation purpose, but it needs review because it can run unsafe shell searches from user-provided topics and persist sensitive education context locally.
LLM: suspicious (high) · VirusTotal: suspicious · 10 Sept 2026