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Install: clawhub install ashanzzz-vikunja-task-api Full Vikunja v2 API integration — projects, tasks, labels, teams, views, comments, attachments, bulk operations, and more.

ClawHub Agent Skills author: Meng v2.5.1 MIT-0 4 files · 1 script body ≈ 4 827 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationInfrastructuretype 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
C
73/100
safety, quality, tests
Safety 60%
75
Quality 40%
71
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
When it triggers w 12
20
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.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Dangerous commands cmd-shell-rc SKILL.md:112
    Writes to a shell startup file
    echo 'export VIKUNJA_URL="http://your…456"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:113
    Writes to a shell startup file
    echo 'export VIKUNJA_TOKEN="tk_your_token"' >> ~/.bashrc
  • medium Exfiltration net-credential-use vikunja.sh:69
    Credential used in a network call (verify the destination is the intended service)
    curl -fsS "$VIKUNJA_URL$path" -H "Authorization: Bearer $VIKUNJA_TOKEN"
  • medium Exfiltration net-credential-use vikunja.sh:104
    Credential used in a network call (verify the destination is the intended service)
    curl -fsS -X DELETE "$VIKUNJA_URL$path" -H "Authorization: Bearer $VIKUNJA_TOKEN"
  • medium Exfiltration net-credential-use vikunja.sh:159
    Credential used in a network call (verify the destination is the intended service)
    curl -fsS "$VIKUNJA_URL/projects" -H "Authorization: Bearer $VIKUNJA_TOKEN" \

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4827 tokens
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 15 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 174: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (32 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This appears to be a real Vikunja task-management integration, but it documents broad write/delete/sharing powers and recommends credential persistence in a way users should review carefully.
LLM: suspicious (high) · VirusTotal: · 29 May 2026