path-tracing
SKILL.md
Path Tracing and Ray Tracing Implementation
This skill provides guidance for implementing path tracers and ray tracers, particularly for image reconstruction tasks where a target image must be matched within a similarity threshold.
When to Use This Skill
- Implementing ray tracers or path tracers in C/C++
- Reconstructing images by reverse-engineering scene parameters
- Building rendering systems with geometric primitives (spheres, planes)
- Tasks requiring image similarity matching (L2 norm, cosine similarity)
- Rendering scenes with shadows, reflections, or procedural textures
Workflow: Baseline-First Development
Phase 1: Establish a Working Baseline
Before any optimization or parameter tuning, establish a complete working render:
- Start with minimal samples - Use S=1 or S=2 to verify the pipeline produces complete output
- Verify output file completeness - Check that the output file contains valid, complete image data before proceeding
- Test in target environment early - If the task specifies a chroot jail, sandbox, or specific execution environment, test there immediately
- Fix all compiler warnings first - Treat warnings as errors; typos like
doubledinstead ofdouble dcause undefined behavior
Phase 2: Scene Analysis
When reconstructing from a reference image:
- Read and parse image header - Extract dimensions, format, color depth
- Sample key pixels systematically - Sample corners, center, and regions of interest
- Identify scene elements - Count all objects (spheres, planes, lights) before implementing
- Analyze gradients and patterns - Sample multiple points to derive mathematical relationships for sky gradients, floor patterns
- Document derived parameters - Write down calculated values (camera FOV, sphere position/radius, light direction)
Phase 3: Incremental Implementation
- One feature at a time - Add sphere, then floor, then shadows, then soft shadows
- Validate each addition - Render and compare after each feature
- Calculate render time before choosing sample count - For a 2400×1800 image at 50 samples, estimate:
pixels × samples × rays_per_sample × time_per_ray - Never modify code while renders are running - This creates race conditions and confusion about which version produced which output
Phase 4: Validation
- Use the exact similarity metric - If grading uses normalized L2 or cosine similarity, compute that metric, not RMS error or other proxies
- Create a reusable validation script early - Avoid rewriting comparison code repeatedly
- Verify output file before submission - Check file size, parse the image, confirm dimensions match expected
Common Scene Elements
Sky Gradients
Analyze by sampling multiple y-coordinates at a fixed x to derive the vertical gradient formula. Sample multiple x-coordinates at a fixed y to check for horizontal variation.
Checkered Floor
To match checker patterns:
- Sample points across the floor to determine checker scale
- Identify the checker color values precisely
- Verify pattern origin and orientation
Spheres
Derive sphere parameters by:
- Finding the visual center of the sphere in image coordinates
- Estimating radius from the sphere's apparent size
- Calculating reflection and shadow geometry to verify position
Shadows
- Hard shadows: Single ray to light source
- Soft shadows: Multiple samples with jittered light directions
- Verify shadow direction matches light position
Time Management
Calculate Expected Render Time First
render_time ≈ (width × height × samples × bounces) / rays_per_second
Typical ray tracer performance: 100K-1M rays/second depending on scene complexity.
For a 2400×1800 image:
- S=1: ~4M rays, seconds to complete
- S=10: ~40M rays, minutes to complete
- S=50: ~200M rays, could take 10+ minutes
- S=100: ~400M rays, may exceed time limits
Adjust Parameters for Time Budget
If the task has a time limit:
- Calculate maximum feasible sample count
- Start with that limit, not above
- Consider rendering at lower resolution first for validation
Common Pitfalls to Avoid
Code Quality Issues
- Typos in type declarations -
doubledvsdouble dcauses undefined behavior - Ignoring compiler warnings - Fix all warnings before running long processes
- Race conditions - Never edit code while a render is still running
Validation Mistakes
- Wrong similarity metric - Match the exact metric used for grading
- Incomplete output files - Always verify file completeness before considering done
- Downsampled validation - If final output must be full resolution, validate at full resolution
Time Management Mistakes
- Starting with high sample counts - Always start low (S=1) to verify correctness
- Not calculating expected render time - Lead to timeout and wasted iterations
- Iterating without completing - Better to have one complete low-quality render than many incomplete high-quality attempts
Analysis Mistakes
- Missing scene elements - Thoroughly identify all objects before implementing
- Arbitrary parameter guessing - Derive parameters mathematically from reference image samples
- Sign errors in gradients - Double-check gradient direction by sampling multiple points
Verification Checklist
Before considering the task complete:
- Code compiles without warnings
- Output file exists and is complete (correct size, valid format)
- Output dimensions match expected dimensions
- Similarity metric meets the required threshold
- Tested in the target execution environment
- All scene elements from reference are present in output
Weekly Installs
20
Repository
letta-ai/skillsFirst Seen
Jan 23, 2026
Security Audits
Installed on
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