AgentDbg

What it does

Record agent runs to local JSONL and inspect a timeline of LLM calls, tool calls, state, and errors. Includes loop warnings. No cloud, no accounts, no telemetry. 1. Timeline UI for LLM/tool calls/errors/state 2. Loop warnings for repetitive behavior 3. Redaction on by default + truncation limits 4. Works with any Python; optional LangChain/LangGraph handler 5. Export runs to a single JSON

Your agent still returns the right answer -- but now it calls 3x the tools. Maida is the pre-merge behavioral regression gate for AI agents: baseline agent traces, gate PRs in CI, block behavior regressions before merge. Local-first, no cloud. - maida-ai/maida

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  Agents.json – OpenAPI Specification for LLMs2025 · github.com · ▲212

  Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…

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  Progress AI ObservabilityAug 2026 · telerik.com · ▲168

  Hi HN! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.

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  Agentflow – Run Complex LLM Workflows from Simple JSON2023 · github.com · ▲51

  So, it feels like this should exist. But I couldn't find it. So I tried to build it. Agentflow lets you run complex LLM workflows from a simple JSON file. This can be as little as a list of tasks. Tasks can include variables, so you can reuse workflows for different outputs by providing different variable values. They can also include custom functions, so you can go beyond text generation to do anything you want to write a function for. Someone might say: "Why not just use ChatGPT?" Among other reasons, I'd say that you can't template a workflow with ChatGPT, trigger it with different…

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