ffmpeg-graceful-degradation

Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies

Quality

66%

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Securityby

Passed

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tessl review fix ./benchmarks/gdpval/skills/ffmpeg-graceful-degradation/SKILL.md

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with executable ffmpeg/moviepy code and a well-sequenced fallback workflow that includes validation and error-recovery loops. Its weaknesses are redundant restatements of the same workflow across multiple sections and a monolithic structure with no reference files despite content that would benefit from being split out.

Suggestions

Collapse the redundant restatements — keep one of the Overview, Decision Flow, or Key Principles sections and trim the others to remove padding.

Move the full `safe_video_encode` implementation into a bundled script (e.g. scripts/safe_encode.py) and the error-pattern table into a references file, leaving SKILL.md a lean overview.

Make the test-clip validation a hard pass/fail gate and reflect it inside the reference implementation so the described workflow and the code stay consistent.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with executable code blocks, but the same four-step workflow is restated across the intro, Overview, Steps 1-4, the ASCII Decision Flow, and Key Principles — several padded/redundant sections that could be tightened, matching 'mostly efficient but includes some unnecessary explanation' rather than a 4.	3 / 5
Actionability	Provides fully executable, copy-paste-ready guidance throughout: the `ffmpeg -encoders \| grep` probe, the 5-second test-clip extraction, copy/mpeg4 fallback commands, a moviepy snippet, and a complete `safe_video_encode` reference function covering the common cases.	5 / 5
Workflow Clarity	Clear sequenced steps with a validation checkpoint ('Never start batch processing without validation... test a short segment', 'Check the exit code') and a progressive-fallback feedback loop, but the reference `safe_video_encode` implementation omits the test-clip gate it emphasizes, leaving a minor validation gap that keeps it below 5.	4 / 5
Progressive Disclosure	Section structure is decent, but with no bundle files present the entire body (~200 lines, including a full implementation function and an error-pattern table that could live in separate reference/script files) is inlined in SKILL.md; the >50-line simple-skill exception does not apply, so it sits at 'some structure but content that should be separate is inline'.	3 / 5
	Total	15 / 20 Passed

Description

61%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description clearly conveys a focused ffmpeg failure-handling niche with decent trigger terms, but it omits any 'Use when' trigger guidance and only abstractly names its capabilities rather than enumerating concrete actions. Stronger trigger phrasing and an explicit use-when clause would lift completeness and specificity.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers, e.g. 'Use when ffmpeg encoding fails, codecs are missing, or video transcoding errors occur in batch processing.'

Enumerate concrete actions instead of abstract concepts, e.g. 'Probes encoder availability, tests a short clip, and falls back through copy mode, mpeg4, and moviepy.'

Include natural synonyms users say ('video transcoding', 'codec errors', 'video processing') to broaden trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Quotes 'Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies' — it names the domain (ffmpeg encoding failures) and a couple of capability concepts (degradation workflow, progressive fallback), but does not enumerate the concrete actions (probe encoders, test clip, copy mode, mpeg4, moviepy), so it lands at 'names domain and 1-2 concrete actions, not comprehensive' rather than a 4.	3 / 5
Completeness	It clearly states what ('Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies') but provides no 'Use when...' clause or equivalent explicit trigger guidance; per the judging guideline a missing 'when' caps completeness at 3.	3 / 5
Trigger Term Quality	Includes natural user-facing terms 'ffmpeg' and 'encoding failures' plus 'fallback strategies'; a few common variations a user might say (transcode, video processing, codec errors) are missing, matching 'good keyword coverage; a few natural terms missing' rather than the comprehensive 5.	4 / 5
Distinctiveness Conflict Risk	'ffmpeg encoding failures' carves a clear, narrow niche unlikely to trigger for unrelated skills, but without explicit 'Use when' trigger phrases the boundary is slightly soft, placing it at 'mostly distinct; minor overlap risk' rather than the fully bounded 5.	4 / 5
	Total	14 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: HKUDS/OpenSpace
Path: benchmarks/gdpval/skills/ffmpeg-graceful-degradation/SKILL.md
Commit: 3827781

Reviewed: 10 days ago

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