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Implements hub-and-spoke lazy loading to minimize token usage in large skills.
Passed 20 of 20 test cases with the skill, and 4 of 20 without it.
and 21 more in the full report
18 fixed4 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
When an incoming repository contains a pyproject.toml or poetry.lock file, which module standard pattern file should be loaded dynamically by the hub?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies loading modules/python-packaging.md. | Missed | Passed |
The instructions your model reads when the skill loads.
Progressive loading provides standardized patterns for building skills that load modules dynamically based on context, user intent, and available token budget. This prevents loading unnecessary content while ensuring required functionality is available when needed.
The core principle: Start minimal, expand intelligently, monitor continuously.
Use progressive loading when building skills that:
## Progressive Loading
**Context A**: Load `modules/loading-patterns.md` for scenario A
**Context B**: Load `modules/selection-strategies.md` for scenario B
**Always Available**: Core utilities, exit criteria, integration points
Verification: Run the command with --help flag to verify availability.
Modules are declared in the skill's YAML frontmatter and
loaded on demand with a @modules/ directive. The hub reads
test cases passed, vs 4 / 20 without
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