CC Seal and License Workflows or Skill Packages (Anti-Piracy, Node-Authorized Delivery)
For small-system and workflow local delivery scenarios: seal Python script collections into single-node-authorized local packages. Scripts keep their original code (import / relative paths / subprocess all supported) — MGC 1.5.2 auto-routes through sealed execution. Delivered packages cannot be read, modified, or resold. Zero cloud, zero exposure.
For small-system and workflow local delivery scenarios: seal Python script collections into single-node-authorized local packages.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
How to improve
- 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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
name-longname is longer than 64 chars - warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 5, column 14: description: For small-system and workflow local delivery scenarios: seal Pytho… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "spec" - note
frontmatter-keyunknown frontmatter key "id" - note
frontmatter-keyunknown frontmatter key "platform_compatibility" - note
frontmatter-keyunknown frontmatter key "mcp_tools" - note
frontmatter-keyunknown frontmatter key "install" - note
frontmatter-keyunknown frontmatter key "runtime" - note
frontmatter-keyunknown frontmatter key "port" - note
frontmatter-keyunknown frontmatter key "changelog"
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (Seal and License Workflows or Skill Packages (Anti-Piracy, Node-Authorized Delivery)) differs from the folder (seal-and-license-workflow-skills)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 34 steps
- 100Execution cost. Instruction body is 3886 tokens
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- -227 emoji in the instructions: noise for the model
- +2Single-language instructions
- +3Description length 349: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (9 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.