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Transform vague prompts into actionable specs using intelligent analysis and session memory.
Passed 20 of 22 test cases with the skill, and 3 of 22 without it.
and 32 more in the full report
19 fixed1 passed either way0 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 19 test cases the skill fixed. Same model, same prompt, with and without the skill.
Fix typo in error message string inside user signup handler. -e
| Checked | Without skill | With skill |
|---|---|---|
| The output includes the INTENT: field label. | Missed | Passed |
| The output includes the ACTION: field label. | Missed | Passed |
| The output omits the METRICS: optional field. | Passed | Passed |
The instructions your model reads when the skill loads.
Transform: Vague intent → Structured specification (Memory-based, Direct Output)
Languages: English + Chinese (中英文语义识别)
Internal Analysis: Intelligently extract session context, identify tech stack, and structure into actionable format.
Output: Direct structured prompt (no intermediate steps shown)
Dynamic Structure: Adapt fields based on task type and context needs. Not all fields are required.
Core Fields (always present):
Optional Fields (include when relevant):
Example (Simple Task):
📋 ENHANCED PROMPT
INTENT: Fix authentication token validation in JWT middleware
ACTION:
test cases passed, vs 3 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.