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AC limesurvey

Automate LimeSurvey operations via RemoteControl 2 API. Use when: (1) managing surveys, questions, groups, or participants, (2) exporting responses or statistics, (3) sending invitations or reminders, (4) importing surveys or questions, (5) batch operations on survey data. Supports JSON-RPC API with full CRUD operations for surveys, participants, responses, questions, and groups. **REQUIRED ENVIRONMENT VARIABLES:** LIMESURVEY_URL (your RemoteControl endpoint), LIMESURVEY_USER, LIMESURVEY_PASSWORD (use least-privilege service account, never full admin credentials).

ClawHub Agent Skills author: Daniel Marques v1.2.2 MIT-0 7 files body ≈ 2 765 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, consistency, running it twice

IntegrationData and analyticsInfrastructureResearchtype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
60/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 7. 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 60/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 18 mutating operations with no state check
    • 40Consistency. Frontmatter name (limesurvey) differs from the folder (limesurvey-openclaw-skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 52 steps
    • 100Execution cost. Instruction body is 2765 tokens

    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)
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 570: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 52 items
    • +3Output format is stated explicitly
    • +4Has examples (25 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate LimeSurvey automation skill, but it can export sensitive survey data, send participant emails, and change or delete survey records with limited built-in safeguards.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026