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AC cursor-agent

Launch and manage Cursor Cloud Agents via the official API v0. Use when user asks to delegate a coding task to Cursor's cloud agent, create a PR automatically, or track agent progress. Requires python3 and a Cursor API key stored in ~/.cursor_api_key.

ClawHub Agent Skills author: siaslfs v1.1.0 5 files body ≈ 1 499 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

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

IntegrationAI and agentsSoftware developmenttype 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%
100
Quality 40%
83
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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: 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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 13 mutating operations with no state check
    • 40Consistency. Frontmatter name (cursor-agent) differs from the folder (cursor-cloud-agent)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 39 steps, 1 vague phrases
    • 100Failures and branches. 3 branches, has a failure section
    • 100Execution cost. Instruction body is 1499 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)
    • +3Output format is not stated: the model decides each time
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 251: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 39 items
    • +4Has examples (6 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This skill mostly does what it says, but it also starts an under-disclosed background watcher with a Cursor API key and can send task details to Feishu.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026