pinchbenchRun PinchBench benchmarks to evaluate OpenClaw agent performance across real-world tasks. Use when testing model capabilities, comparing models, submitting b...
Install via ClawdBot CLI:
clawdbot install olearycrew/pinchbenchGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
report → https://docs.mycompany.com/alpha-security-reviewPotentially destructive shell commands in tool definitions
eval (Accesses system directories or attempts privilege escalation
/var/log/Calls external URL not in known-safe list
https://pinchbench.comGenerated Mar 21, 2026
AI researchers and developers use PinchBench to evaluate and compare different LLM models integrated into OpenClaw agents. They run automated benchmarks across tasks like calendar management and coding to measure performance, submit results to a public leaderboard, and optimize their agent setups for real-world applications.
Companies implement PinchBench to assess how well AI agents handle internal workflows such as email triage, document summarization, and market research. By running specific task suites, they validate agent reliability, identify weaknesses in productivity and analysis tasks, and ensure robust integration before deployment.
Educational institutions and training programs use PinchBench to teach students about AI agent capabilities through hands-on benchmarking. Learners run tasks like blog writing and file management to understand model performance, analyze results with JSON tools, and develop custom tasks to enhance practical AI skills.
Open-source contributors leverage PinchBench to test and improve AI agents by adding custom tasks for new domains like creative image generation or knowledge management. They share benchmark results on the leaderboard, collaborate on task development, and drive innovation in agent performance standards.
Offer PinchBench as a cloud-based service where users pay subscription fees to access advanced benchmarking features, detailed analytics, and premium leaderboard rankings. Revenue is generated through tiered plans for individuals, teams, and enterprises seeking continuous performance monitoring and comparison.
Provide consulting services to help businesses integrate and optimize OpenClaw agents using PinchBench benchmarks. Revenue comes from project-based fees for custom task development, performance tuning, and training workshops to improve AI workflow efficiency and reliability.
Distribute PinchBench as a free open-source tool to build a user base, then monetize through premium add-ons like advanced analytics dashboards, priority support, and custom leaderboard features. Revenue is driven by one-time purchases or upgrades for enhanced functionality.
💬 Integration Tip
Ensure Python 3.10+ and uv are installed, then run benchmarks with specific model identifiers and task suites to test agent capabilities efficiently; use the --no-upload flag for internal testing before submitting to the leaderboard.
Scored Apr 19, 2026
AI Analysis
The skill's primary purpose is benchmark execution and result submission to a public leaderboard, which aligns with the documented external endpoint (pinchbench.com). The 'UNKNOWN_DATA_SINK' signal appears to reference an internal security review document, not an active data exfiltration endpoint. No credential harvesting, hidden instructions, or obfuscation are evident in the provided definition.
Audited Apr 16, 2026 · audit v1.0
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