AgentActa
AgentActa is a local audit trail and search engine for AI agent sessions — one command (`npx agentacta`), zero config, that indexes messages, tool calls, file edits, searches, and decisions into a sea
About
AgentActa is a local audit trail and search engine for AI agent sessions — one command (npx agentacta), zero config, that indexes messages, tool calls, file edits, searches, and decisions into a searchable local UI. Born from the problem of "your agent did thousands of things today — can you find the one that broke prod?" It covers session browsing with token breakdowns, full-text search across all events, timeline view with live updates, and project-scoped attribution.
Individual developers and small teams who need to debug what their AI agent did in a specific session — particularly useful after unexpected behavior or production incidents where "what changed, when, and why" needs a fast answer without scraping raw logs.
Pros & Cons
Pros
- check Zero-config local deployment — `npx agentacta` and you're running, no API keys or cloud accounts
- check Full-text search across messages, tool calls, and results makes incident debugging dramatically faster than scrolling transcripts
- check Session browser with token breakdowns and model info gives cost visibility alongside behavioral audit
- check Timeline view with live updates supports active monitoring during agent runs, not just post-hoc review
- check MIT licensed with 60 commits — small but actively developed
Cons
- close Local-only — no team sharing, cloud sync, or cross-machine audit trail access
- close Only 6 stars on GitHub at time of review — very early adoption, community and maintenance uncertain
- close Doesn't integrate directly with agent runtimes for live interception — relies on indexed session data
- close Limited to session data structure; doesn't correlate agent decisions with downstream production effects
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