| --- |
| agent_name: "React + Shortlisting" |
| version: "exgentic 0.1.0 / litellm 1.79.1" |
| developers: "Exgentic Team" |
| license: "Apache-2.0" |
| framework: "Exgentic" |
| repository: "https://github.com/Exgentic/exgentic" |
| models: |
| - "Claude Opus 4.5" |
| - "GPT-5.2" |
| - "Gemini Pro 3" |
| tags: |
| - agent |
| - react |
| - tool-calling |
| - general-purpose |
| --- |
| |
| # React + Shortlisting |
|
|
| > A general-purpose ReAct agent with tool shortlisting -- helps the agent focus on relevant tools instead of searching through everything. |
|
|
| ## Agent Details |
|
|
| - **Name**: React + Shortlisting |
| - **Version**: exgentic 0.1.0 / litellm 1.79.1 |
| - **Developers**: Exgentic Team |
| - **Framework**: [Exgentic](https://github.com/Exgentic/exgentic) |
| - **License**: Apache-2.0 |
|
|
| ## Architecture |
|
|
| ### Planning |
| ReAct (Reasoning + Acting) loop: the agent reasons about the current state, selects an action, observes the result, and repeats. |
|
|
| ### Memory |
| Full conversation history within the session. No cross-session memory. |
|
|
| ### Tool Use |
| Function calling via LiteLLM. Before each step, a shortlisting phase narrows the available tools to the most relevant subset for the current task context. This reduces noise and improves action selection, especially in benchmarks with large action spaces. |
|
|
| ### Error Recovery |
| Retry on transient failures. The agent can observe error messages and adjust its approach on subsequent steps. |
|
|
| ### Subagents |
| None -- single-agent system. |
|
|
| ## Models |
|
|
| | Role | Model | Purpose | |
| |------|-------|---------| |
| | Main | Claude Opus 4.5 / GPT-5.2 / Gemini Pro 3 | Reasoning, action selection, tool calls | |
|
|
| ## Supported Environments |
|
|
| - AppWorld (app-based task completion) |
| - BrowseComp+ (web research) |
| - SWE-bench (software engineering) |
| - TauBench Airline, Retail, Telecom (customer service) |
|
|
| ## Evaluation Results |
|
|
| | Benchmark | Score (Opus 4.5) | Score (Gemini Pro 3) | Avg Cost (Opus 4.5) | |
| |-----------|-------------------|----------------------|----------------------| |
| | AppWorld | 0.66 | 0.40 | $7.80 | |
| | SWE-bench | 0.49 | 0.36 | $3.64 | |
| | TauBench-Airline | 0.56 | 0.59 | $0.96 | |
| | TauBench-Retail | 0.72 | 0.72 | $1.06 | |
|
|
| **Full results**: [Open Agent Leaderboard](https://huggingface.co/spaces/open-agent-leaderboard/leaderboard) |
|
|
| ## Cost Profile |
|
|
| The most cost-efficient configuration in the top 5 on the leaderboard. With Gemini Pro 3, average cost per task is $0.66 -- a fraction of other top agents. Tool shortlisting reduces unnecessary tool calls, directly lowering cost. |
|
|
| ## Limitations |
|
|
| - No cross-session memory or learning |
| - Performance depends heavily on the quality of tool descriptions |
| - Shortlisting may occasionally filter out a relevant tool in novel contexts |
|
|
| ## How to Run |
|
|
| ```bash |
| uv tool install exgentic |
| |
| exgentic evaluate \ |
| --benchmark tau2 \ |
| --subset retail \ |
| --agent tool_calling_with_shortlisting \ |
| --model openai/claude-opus-4-5 |
| ``` |
|
|
