yaojingang
1.6 KiB
1.6 KiB
Intent Confidence
- Confidence score:
30/100 - Confidence band:
low - Gate passed:
False - Recommended action: Pause before deep authoring and close the highest-leverage gaps first.
Current Reading
Create, refactor, evaluate, and package agent skills from workflows, prompts, transcripts, docs, or notes. Use when asked to create a skill, turn a repeated process into a reusable skill, improve an existing skill, add evals, or package a skill for team reuse.
Strong Signals
- The recurring job is concrete enough to anchor the package.
Gaps To Close
- Real inputs are missing (
high): Without real inputs, it is hard to choose assets, scripts, or examples. - Primary output is missing (
high): The package does not yet know what it must hand back. - Near-neighbor exclusions are missing (
high): The route may blur into nearby requests without an exclusion list. - Constraints are missing (
high): The package does not yet know which tradeoffs matter most. - Quality bar is implied, not explicit (
medium): The first evaluation target is still underspecified.
Follow-Up Questions
- What material will people actually hand to this skill in practice?
- Why: Real input shape decides whether references, scripts, or examples are needed.
- What finished hand-back should this skill return so the next person can keep moving?
- Why: The output is the anchor for package design and review.
- What nearby requests should this skill clearly leave out so the boundary stays clean?
- Why: Exclusions are the fastest route to better trigger quality.