AgentLedger records reputation events and computes transparent trust scores for AI agents. It answers: how has this agent performed over time?
AgentLedger is open, append-only infrastructure. Any platform may submit signed events; any verifier may recompute scores from the published formula.
Use it with AgentID and AgentCert for a complete trust stack.
- Append-only — events are never mutated in place
- Transparent scoring — published formula, auditable output
- Persistent — SQLite storage in v0.1
- Privacy-aware — stores comment hashes instead of raw text by default
pip install -r requirements.txt
python cli.py add-event \
--agent-id did:agent:demo123456 \
--type task_completed \
--rating 5 \
--comment "Booked restaurant successfully"
python cli.py get-score --agent-id did:agent:demo123456
python cli.py list-events --agent-id did:agent:demo123456 --limit 10| Type | Meaning |
|---|---|
task_completed |
Successful execution |
task_failed |
Failed execution |
user_rating |
User-provided rating |
complaint |
Negative report |
complaint_resolved |
Complaint closed |
verification_passed |
Passed verification |
| Project | Role |
|---|---|
| AgentID | Decentralized agent identity |
| AgentCert | Verifiable trust credentials |
Apache-2.0 — see LICENSE.
AgentLedger 记录 Agent 信誉事件并计算透明的信任评分,回答:这个 Agent 长期表现如何?
AgentLedger 是开放的只追加基础设施。任何平台都可提交签名事件;任何验证方都可依据公开公式重算评分。
与 AgentID、AgentCert 组合,可形成完整信任栈。
- 只追加 — 事件写入后不在原处修改
- 评分透明 — 公开公式,结果可审计
- 持久化 — v0.1 使用 SQLite 存储
- 隐私友好 — 默认仅存评论哈希,不存原文
pip install -r requirements.txt
python cli.py add-event \
--agent-id did:agent:demo123456 \
--type task_completed \
--rating 5 \
--comment "餐厅预订成功"
python cli.py get-score --agent-id did:agent:demo123456
python cli.py list-events --agent-id did:agent:demo123456 --limit 10| 类型 | 含义 |
|---|---|
task_completed |
任务成功 |
task_failed |
任务失败 |
user_rating |
用户评分 |
complaint |
投诉 |
complaint_resolved |
投诉已解决 |
verification_passed |
通过核验 |
| 项目 | 角色 |
|---|---|
| AgentID | 去中心化 Agent 身份 |
| AgentCert | 可验证信任凭证 |
Apache-2.0 — 见 LICENSE。