SKILLEMALL.ai

BC obsidian-librarian

Obsidian second-brain and knowledge-base skill. Save any URL, article, tweet, or X post to your Obsidian vault as clean, categorized, wikilinked markdown. Two-pass Gemini pipeline handles structure, tags, and categories. Ask your whole vault anything with RAG, backed by a local JSON index or Supabase pgvector. URL fetch via Apify. Triggers on "save this", "save it", "save this url", research capture, vault search, or querying saved notes.

ClawHub Agent Skills author: shahalay007 v0.2.7 MIT-0 21 files · 17 scripts body ≈ 1 403 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Obsidian second-brain and knowledge-base skill.

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureObsidianSupabaseAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
62/100
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. 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 · 0

✓ No critical or high findings

Files scanned: 21. 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 62/100

  • 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. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 41 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1403 tokens
  • high The skill tells the model to perform an irreversible action with no human approval

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -315 of 17 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 442: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 41 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill broadly matches its Obsidian knowledge-base purpose, but it can send private notes or files to external services and has path-scope flaws that could read or delete files outside the intended vault inbox.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026