SKILLEMALL.ai

BB social-media-favorites-archiver

Sync a user's Bilibili/B站, Xiaohongshu/小红书/RedNote, and Douyin/抖音 favorites into local Markdown/Obsidian with local ASR/OCR.

ClawHub Agent Skills author: dvlin v1.0.4 MIT-0 8 files body ≈ 1 146 tokens Open the sourceclawhub.ai analyzed 3 d ago

Sync a user's Bilibili/B站, Xiaohongshu/小红书/RedNote, and Douyin/抖音 favorites into local Markdown/Obsidian with local ASR/OCR.

As a process B 66/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureObsidianMarketingSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
77
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-persistence references/troubleshooting.md:41
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (quoted — discussed, not commanded)
    Save as `~/Library/LaunchAgents/dev.smfa.sync.plist`, then load it with `launchctl bootstrap gui/$(id -u) ~/Library/LaunchAgents/dev.smfa.sync.plist`:
    quoted

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 66/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 21 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 1146 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • +2Single-language instructions
  • +3Description length 124: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill is a clearly scoped local archiving workflow for a user's own social-media favorites, with sensitive account and enrichment handling disclosed and bounded.
LLM: benign (high) · VirusTotal: · 9 Aug 2026