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README.md

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+---
+license: apache-2.0
+task_categories:
+  - text-generation
+language:
+  - en
+tags:
+  - benchmark
+  - ai-agents
+  - cli
+  - tool-use
+  - evaluation
+pretty_name: "CLI-Bench"
+size_categories:
+  - n<1K
+---
+
+# CLI-Bench: Benchmarking AI Agents on CLI Tool Orchestration
+
+CLI-Bench is a benchmark for evaluating the ability of AI agents (e.g., LLM-based coding assistants) to use command-line interface tools to accomplish real-world developer tasks. Unlike existing benchmarks that focus on code generation or isolated API calls, CLI-Bench tests whether agents can **orchestrate multiple CLI tools** end-to-end across realistic workflows spanning project management, DevOps, communication, and data operations.
+
+## Overview
+
+| Property | Value |
+|---|---|
+| **Tasks** | 40 |
+| **Categories** | 6 (devops, project_mgmt, communication, data_ops, custom_cli, composite) |
+| **Tool Adapters** | 12 (7 real-world + 5 fictional) |
+| **Difficulty** | 20 easy, 10 medium, 10 hard |
+| **Format** | YAML task definitions with declarative initial/expected state |
+
+## Task Categories
+
+- **devops**: Infrastructure and deployment operations (CI/CD, monitoring, alerts)
+- **project_mgmt**: Issue tracking, sprint management, task coordination across platforms
+- **communication**: Messaging, notifications, channel management via Slack and email
+- **data_ops**: Data pipeline construction, ETL operations, report generation
+- **custom_cli**: Tasks using fictional CLIs that cannot be memorized from training data
+- **composite**: Multi-tool workflows requiring coordination across 2-3 tools in sequence
+
+## Tool Adapters
+
+### Real-World Tools (7)
+| Tool | Domain |
+|---|---|
+| `gh` | GitHub CLI (issues, PRs, repos, actions) |
+| `slack` | Slack CLI (messages, channels, users) |
+| `linear` | Linear CLI (issues, projects, cycles) |
+| `notion` | Notion CLI (pages, databases, blocks) |
+| `google` | Google Workspace (Gmail, Calendar, Drive) |
+| `jira` | Jira CLI (issues, sprints, boards) |
+| `microsoft` | Microsoft 365 (Teams, Outlook, OneDrive) |
+
+### Fictional Tools (5) — Memorization-Proof
+| Tool | Domain |
+|---|---|
+| `kforge` | Artifact registry and deployment management |
+| `flowctl` | Workflow engine with approval gates |
+| `meshctl` | Service mesh topology and traffic control |
+| `datapipe` | Declarative ETL pipeline builder |
+| `alertmgr` | Alert routing, escalation, and incident management |
+
+Fictional tools are designed so that agents **cannot rely on memorized CLI syntax** from pre-training. Agents must read the provided tool adapter specifications and reason about correct usage from first principles.
+
+## Task Format
+
+Each task is a YAML file containing:
+
+```yaml
+id: cb-001
+title: "List open issues in a GitHub repo"
+difficulty: easy
+category: project_mgmt
+description: |
+  Natural language description of the task objective.
+tools_provided:
+  - gh
+initial_state:
+  gh:
+    repos:
+      acme-corp/web-platform:
+        issues:
+          - number: 42
+            title: "Fix login redirect loop"
+            state: open
+            assignee: alice
+expected_state:
+  gh:
+    command_history:
+      - pattern: "gh issue list.*--repo acme-corp/web-platform.*--state open"
+    output_contains:
+      - "42"
+scoring:
+  outcome: 0.6
+  efficiency: 0.2
+  recovery: 0.2
+```
+
+- **initial_state**: The simulated environment state before the agent acts.
+- **expected_state**: Declarative assertions on command patterns, state mutations, and expected outputs.
+- **scoring**: Per-task weight overrides for the three evaluation dimensions.
+
+## Evaluation Metrics
+
+CLI-Bench scores agents along three dimensions:
+
+| Metric | Weight (default) | Description |
+|---|---|---|
+| **Outcome** | 0.6 | Did the agent achieve the desired end state? Verified via declarative state assertions. |
+| **Efficiency** | 0.2 | Did the agent use a reasonable number of commands? Penalizes excessive retries or unnecessary exploration. |
+| **Recovery** | 0.2 | Did the agent handle errors or unexpected states gracefully? Tests resilience to failed commands and ambiguous outputs. |
+
+The aggregate score per task is a weighted sum. The benchmark also reports **pass^k** (the fraction of tasks solved within *k* attempts), providing a measure of reliability across repeated runs.
+
+## Difficulty Levels
+
+- **Easy (20 tasks)**: Single-tool, single-command operations with straightforward state assertions.
+- **Medium (10 tasks)**: Single-tool multi-step workflows or tasks requiring conditional logic.
+- **Hard (10 tasks)**: Multi-tool composite workflows requiring sequential orchestration, error recovery, and cross-tool state propagation.
+
+## Usage
+
+### With the `datasets` library
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("ChengyiX/CLI-Bench")
+```
+
+### Loading YAMLs directly
+
+```python
+import yaml
+from pathlib import Path
+
+tasks = []
+for task_file in sorted(Path("data/tasks").glob("cb-*.yaml")):
+    with open(task_file) as f:
+        tasks.append(yaml.safe_load(f))
+
+print(f"Loaded {len(tasks)} tasks")
+print(f"Categories: {set(t['category'] for t in tasks)}")
+```
+
+### Loading tool adapter specifications
+
+```python
+import yaml
+from pathlib import Path
+
+adapters = {}
+for adapter_file in Path("tool_adapters").glob("*.yaml"):
+    with open(adapter_file) as f:
+        adapter = yaml.safe_load(f)
+        adapters[adapter_file.stem] = adapter
+
+print(f"Loaded {len(adapters)} tool adapters")
+```
+
+## Repository Structure
+
+```
+data/
+  metadata.yaml          # Benchmark metadata and configuration
+  tasks/
+    cb-001.yaml          # Individual task definitions
+    cb-002.yaml
+    ...
+    cb-040.yaml
+tool_adapters/
+    gh.yaml              # GitHub CLI adapter spec
+    slack.yaml           # Slack CLI adapter spec
+    ...
+    kforge.yaml          # Fictional: artifact management
+    flowctl.yaml         # Fictional: workflow engine
+    meshctl.yaml         # Fictional: service mesh
+    datapipe.yaml        # Fictional: ETL pipelines
+    alertmgr.yaml        # Fictional: alert management
+```
+
+## Citation
+
+```bibtex
+@misc{cli-bench-2026,
+  title={CLI-Bench: Benchmarking AI Agents on Command-Line Tool Orchestration},
+  author={Chengyi Xu},
+  year={2026},
+  url={https://github.com/minervacap2022/CLI-Bench}
+}
+```
+
+## Links
+
+- **GitHub**: [https://github.com/minervacap2022/CLI-Bench](https://github.com/minervacap2022/CLI-Bench)
+- **License**: Apache 2.0