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AB videodb

Video and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and create real-time alerts.

sickn33/agentic-awesome-skills Hermes author: sickn33 MIT 12 files body ≈ 3 402 tokens Open the sourcegithub.com↗ analyzed 23 h ago

Video and audio perception, indexing, and editing.

As a process B 76/100 · Nearly there — weak spots: result and completion, progress reporting

GeneratorMedia and videoResearchAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code Hermes Agent
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
76/100
Nearly there
Progress reporting w 2
0
Result and completion w 14
40
When it triggers w 12
50
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
For the model run — optional
  • 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

  • warning description-long-hermes description is 220 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "risk"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "date_added"

Process rating: all ten parameters 76/100

  • 0Progress reporting. Says nothing while it works
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 60 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3402 tokens
  • 100Running it twice. Mutating operations check current state
  • low 17 top-level sections: this looks like several domains in one skill

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 220: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 60 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: 82.