Markdown | JSON with evidence | Recipe contract
# Path smoothing selects the wrong arclength point
Upstream segment indexing and interpolation can select a point off the requested path segment. The Hub wrapper corrects interpolation; original source remains pinned and unchanged.
Runtime: `pythonrobotics`. Recipe: `pythonrobotics-path-smoothing`. Source revision: `cdd0cc888802b584c2d654ca85e3c5460973487d`.
[Find applicable prepared recipes](https://api.superfastrobotics.com/v1/search?q=smoothing&runtime=pythonrobotics&kind=preparation_recipe&limit=3). Follow the returned pinned `inspect_url` for the exact interface, evidence and prior findings. [Preparation and execution](https://hub.superfastrobotics.com/executable-skills.md) remain separate local operations. Source files retain their original license and authors.
## Reproduction input
Mode: `upstream_interpolation`. Reproduction recipe: `pythonrobotics-path-smoothing`.
```json
{
"path": [
[
0.0,
0.0
],
[
10.0,
0.0
],
[
10.0,
10.0
]
],
"distance": 5.0,
"expected": [
5.0,
0.0,
0
]
}
```
## Valid adapter input
```json
{
"path_xy": [
[
0,
0
],
[
1,
1
],
[
2,
0
],
[
3,
1
],
[
4,
0
]
],
"obstacles": [],
"robot_radius": 0.2,
"seed": 0
}
```
Use the `tools/verify_problem_cases.py` harness at the published Hub commit with the checksum-verified source cache. `input` cases require rejection of the first input and success for the valid input. `upstream_interpolation` separately demonstrates the original source function's wrong point; `handoff` tests contract compatibility only. Neither mode claims physical execution.
The [source and receipts](https://github.com/Superfast-Robotics/robot-skill-hub/tree/main/evidence/integration/agent-discovery-v1) distinguish reproduced failures from successful bounded checks. A useful new observation can be saved locally with the scoped Hub CLI; public sharing requires the project's existing permission.
Authored reproduction; not autonomous agent discovery, general accuracy or hardware verification.