AC videodb
Ingest, index, search, edit, and monitor video and audio with the VideoDB Python SDK — upload from files, URLs, or RTSP feeds, build spoken and scene indexes with timestamped search and playable clips, transcode and reframe, do timeline edits (subtitles, overlays, dubbing), and run real-time alerts on live streams or desktop capture. Use when working with video search, transcription, clipping, transcoding, streaming, or live video alerts.
Promises full video stack: upload, indexing, search, editing, and stream monitoring. Contains 12 files with VideoDB API docs, query examples, and functions for transcoding, clipping, subtitle overlays. Scores solid: quality 91, safety 100, process 63 because sandbox scripts failed to run due to missing videodb module.
In practice: the instruction is sound, but you can't verify it locally without dependencies. Works as a code generation template for Claude, Cursor, and other platforms—the AI will produce correct API calls and video processing workflows. Install it if you plan to work with VideoDB SDK and need a ready reference with working examples.
Ingest, index, search, edit, and monitor video and audio with the VideoDB Python SDK — upload from files, URLs, or RTSP feeds, build spoken and scene indexes…
As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 63/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Inputs and preconditions. Does not say what the process needs to start
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 85Steps. 54 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3353 tokens
- 100Running it twice. Mutating operations check current state
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 442: enough signal without eating the budget
- +4Structure: 33 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (14 code blocks)
- +4Reference files are cited in the instructions (10 of 10)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.
In the sandbox Скрипты не запустились
The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.
Запущено 1 скрипт; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.
Ни один не дошёл до работы — им не хватило зависимостей, аргументов или файлов. Это не отзыв о поведении: наблюдать было не за чем.
scripts/ws_listener.py | не запустился: ModuleNotFoundError: No module named 'videodb' |
6 Oct 2026