SKILLEMALL.ai

BC video-content-operator

Use when a user wants help deciding what video/social content to make, how to package it for different platforms, which source materials or ideas are worth using, or what the next content move should be. This skill is for creator operating decisions above editing execution. It should be used for requests like: plan this week's content, decide which clips are worth turning into posts, package an idea for Xiaohongshu/Shorts/YouTube, generate draft content directions, compare angles, recommend the next post, or analyze a creator's current content situation. Before giving recommendations, first understand the user's current state: who they are, which platforms they are already using, what kinds of content they usually publish, and what problem they are trying to solve. In OpenClaw main sessions, proactively use memory files to understand the user before making recommendations. Do NOT use this skill for pure execution when the user already knows exactly what to edit; defer actual editing to sparki-video-editor or other execution tools.

ClawHub Agent Skills author: fischerlam v0.1.0 MIT-0 10 files body ≈ 1 907 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureYouTubeMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
53
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1046 chars, limit 1024
  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Use when a user wants help deciding what video/social content to m… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Failures and branches. 9 branches
  • 100Steps. 105 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1907 tokens
  • low 12 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
  • +3Description length 1046: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 105 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.

External checks

ClawHub: clean
This skill is a local content-planning helper that can use OpenClaw memory files for personalization, with no evidence of hidden network transfer or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026