Find agent skills by outcome

realism_level: Ultra-realistic

film-grade winter accuracy.

detail: High realism

crisp skin texture

face_visibility: Extreme close-up

fully visible face.

expression: A gentle

warm smile while looking upward.

trees: Tall bare trees bending slightly

forming a natural snowy corridor

identity_cues: Body shape

posture

atmosphere: Quiet

serene winter silence with falling snow

- Assumption Validation: Mark assumptions as validated

pending validation

consistency: Same person across all frames; identical facial structure

skin texture

color_grade: Subtle blue winter grading

cold tones

expression: A warm

natural smile visible from the side profile.

atmosphere: Soft diffused winter light

fine suspended snowflakes

- Project-Scale Adaptation: For full project migrations (Case 3)

expand Project Structure section significantly while keeping other sections concise

- Universality: Structure must be interpretable by any AI platform (ChatGPT

Claude

(... sections continue: Reusable Components

Quality Gates

- Patterns: Prompt chaining

parallelization

- InventorySubAgent

UserAuthSubAgent

- Trigger: Every commit

- Functions: PR feedback

path validation

Ultra-Realistic Winter Cinematography Series

{

- Rule Preservation: When rules/protocols were established during session

include the context of WHY they were needed

Next: Complete PUT/DELETE endpoints

finalize schema

Mitigation: Implement exponential backoff

rotate user agents

Data

Given this context artifact for FitTrack Pro app planning

please design the technical architecture including database schema