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AB obsidian-vault-context

Teach Claude to use an Obsidian vault as a shared workspace with persistent state across sessions. Covers vault navigation, orchestration file management, output routing, and bidirectional collaboration via Obsidian Headless. Use when the agent needs to read vault context, write output to the vault, update status/task files, or navigate folder structure. Triggers on "check status", "what's in the vault", "update tasks", "save this to the vault", "where should I put this", or any vault-related file operation.

ClawHub Agent Skills author: Tristin E v1.0.1 MIT-0 5 files body ≈ 1 046 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, running it twice

GeneratorObsidianAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
94
Quality 40%
92
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Tools and files w 18
60
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

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Dangerous commands cmd-privilege references/obsidian-headless-setup.md:84
      Privilege escalation / world-writable permissions
      sudo tee /etc/systemd/system/obsidian-sync.service << 'EOF'
    • low Dangerous commands cmd-background-process references/obsidian-headless-setup.md:103
      Starts a background / autostarted process
      sudo systemctl enable obsidian-sync

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1046 tokens
    • 100Progress reporting. Reports progress

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 513: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 12 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    The skill appears to be a vault-focused helper whose local file reads and writes are disclosed and purpose-aligned, though users should be careful because it may edit persistent vault files.
    LLM: benign (medium) · VirusTotal: · 29 May 2026