Add Subhound 1.2#1078
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Pull request overview
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Adds a new manifest for the Subhound Sub-GHz application to describe its source location, description/changelog references, and screenshots for catalog/display purposes.
Changes:
- Added
manifest.ymldefining the app’s git source (origin + pinned commit + subdir) - Wired manifest metadata to external markdown files for description and changelog
- Added screenshot entries for UI/catalog previews
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| description: "@CATALOG.md" | ||
| changelog: "@./docs/changelog.md" |
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Hello, I made 2 changes in the app Here is the updated version, you can commit that into your repo and update commit sha here Also btw, why app tries to analyse signal only by using some custom methods when you can try passing that into decoders that are in firmware API ? As an option or maybe before in-app analysis, like in 2 steps, if protocol is unknown we fallback into current analysis functions |
xMasterX
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Update app using provided archive above to fix missing icon and debug logs
Don't forget to change commit sha after that and tag me when its ready
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@xMasterX done, thanks for the patch. Applied your changes and bumped the |
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You need to fix readme / changelog files
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@xMasterX The markdown errors should be resolved now, I've removed the backticks and updated the commit_sha. Thanks! |
Application Submission
Automated classifier for Flipper Zero BinRAW
.subcaptures. Identifies 17 ISM-band signal types — garage remotes, TPMS, weather stations, utility meters, alarm sensors, and more — with reasoning chain and confidence scoring.Initial submission (v1.2). Source: https://github.com/maxwalks/subhound
Extra Requirements
Author Checklist (Fill this out)
python3 tools/bundle.py --nolint applications/CATEGORY/APPID/manifest.yml bundle.zipAI usage disclosure (Fill this out):
Partially AI assisted (clarify below which code was AI assisted and briefly explain what it does).
Fully AI generated (explain what all the generated code does in moderate detail).
AI was used as a coding/writing assistant during development of both the Python reference (
analyze.py) and the C Flipper port (flipper-app/), and to draft the catalog metadata for this submission (CATALOG.md,docs/changelog.md,manifest.yml). All classifier rules, thresholds, and decoder logic were authored, reviewed, and tested by me against real on-device captures. The two implementations are kept in deliberate 1:1 parity with a regression test suite (tests/test_parity.py).Reviewer Checklist (Don't fill this out!)