Overview
- Skill Key
- exe215/agentbench
- Author
- exe215
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/exe215/agentbench
- Latest Commit SHA
- ca3b265a98f7fca906fe5eed361720a63a51ef5f
Benchmark your OpenClaw agent across 40 real-world tasks. Tests file creation, research, data analysis, multi-step workflows, memory, error handling, and tool efficiency. Not a coding benchmark — measures your agent setup and config.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 agentbench 技能。 若已安装,则直接安装 agentbench 技能。
# AgentBench for OpenClaw
Benchmark your OpenClaw agent's general capabilities across 40 real-world tasks spanning 7 domains.
## Commands
When the user says any of these, follow the corresponding instructions:
- **`/benchmark`** — Run the full benchmark suite (all 40 tasks)
- **`/benchmark --fast`** — Run only easy+medium tasks (19 tasks)
- **`/benchmark --suite <name>`** — Run one domain only
- **`/benchmark --task <id>`** — Run a single task
- **`/benchmark --strict`** — Tag results as externally verified scoring
- **`/benchmark-list`** — List all tasks grouped by domain
- **`/benchmark-results`** — Show results from previous runs
- **`/benchmark-compare`** — Compare two runs side-by-side
Flags are combinable: `/benchmark --fast --suite research`
## Running a Benchmark
### Step 1: Discover Tasks
Read task.yaml files from the `tasks/` directory in this skill:
```
tasks/{suite-name}/{task-name}/task.yaml
```
Each task.yaml contains: name, id, suite, difficulty, mode, user_message, input_files, expected_outputs, expected_metrics, scoring weights.
Filter by `--suite` or `--task` if specified. If `--fast` is set and `--task` is not, filter to only tasks where difficulty is "easy" or "medium".
Profile is "fast" if `--fast` was specified, otherwise "full".
List discovered tasks with count and suites.
### Step 2: Set Up Run Directory
Generate a run ID from the current timestamp: `YYYYMMDD-HHmmss`
Read `suite_version` from `skill.json` in this skill directory.
Create the results directory:
```
agentbench-results/{run-id}/
```
Announce: `Starting AgentBench run {run-id} | Profile: {profile} | Suite version: {suite_version} | Tasks: {count}`
### Step 3: Execute Each Task
For each task:
1. **Set up workspace**:
- Create `/tmp/agentbench-task-{task-id}/` as workspace
- Copy input files from `tasks/{suite}/{task}/inputs/` to the workspace (if inputs/ exists)
- If the task directory contains a `setup.sh`: run `bash tasks/{suite}/{task}/setup.sh {wor...
# AgentBench for OpenClaw Benchmark your OpenClaw agent's general capabilities across 40 real-world tasks spanning 7 domains. Not a coding benchmark — tests file creation, research, data analysis, multi-step workflows, memory, error handling, and tool efficiency. Same tasks and scoring as the [Claude Code version](https://github.com/agentbench/agentbench). Results are cross-platform comparable and submit to the same [leaderboard](https://www.agentbench.app/leaderboard). ## Install Place this skill in your OpenClaw skills directory, or clone directly: ```bash git clone https://github.com/agentbench/agentbench-openclaw.git ~/.openclaw/skills/agentbench ``` ## Quick Start ``` /benchmark # Run all 40 tasks (full profile) /benchmark --fast # Run 19 easy+medium tasks (fast profile) /benchmark --suite research # Run one domain /benchmark --suite research --fast # Run easy+medium in one domain /benchmark --task research-summarize-doc # Run one task /benchmark --strict # Tag as externally verified ``` ## Domains | Domain | Tasks | Difficulty | What It Tests | |--------|-------|------------|---------------| | File Creation | 9 | 2E, 3M, 4H | Documents, spreadsheets, project scaffolding, config migration, skill graphs | | Research | 5 | 3M, 2H | Summarize, compare, multi-source synthesis, git archaeology | | Data Analysis | 5 | 1E, 1M, 1H, 1X | Anomalies, statistics, multi-format reconciliation, log pattern detection | | Multi-Step | 5 | 1M, 2H, 2X | Data pipelines, log analysis, repo refactoring, release preparation | | Memory | 5 | 2M, 1H, 1X | Recall, constraints, context switching, progressive accumulation | | Error Handling | 6 | 1E, 2M, 3H | Corrupted input, cascading failures, misleading errors, partial recovery | | Tool Efficiency | 5 | 3E, 2H | Minimal reads, right tool choice, codebase navigation, targeted fixes | *E=Easy, M=Medium, H=Hard, X=Expert* ## Scoring Each t...
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