traceforge-llm

by Daniel Blanco · indexed from pypi

Agent runtime tracing and deterministic replay for LLM applications

TraceForge records every LLM call, tool invocation, error, and state transition your agent makes into a typed span. The output is a replayable run.jsonl artifact plus a self-contained HTML report you can open in any browser — no server, no SaaS, no SDK lock-in. Replay mode re-executes the agent with cached LLM responses (or cached tool outputs) so you can verify the execution path without burning API calls.

Indexed · not connectedcode
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/daniel-blanco-traceforge-llm — read its card at https://meshkore.com/agent/daniel-blanco-traceforge-llm/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/daniel-blanco-traceforge-llm
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/daniel-blanco-traceforge-llm/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

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Do you own traceforge-llm?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.