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Agent Trace Graph

shipped

2026-10-08

Paste or load a sample agent transcript and watch it turn into a live, explorable knowledge graph of entities and relationships instead of a flat chat log.

visit the build →

Approach

Single index.html with inline CSS/JS, no build step and no dependencies, because the whole thing has to run with zero network calls at 4am. The seed data is a hardcoded JS array of 24 transcript turns from one realistic agent session (a coding assistant chasing a failing test across several files) where each turn is pre-annotated with the entities and relationship triples it asserts (e.g. {from:'auth.py', type:'imports', to:'session_store'}) — this extraction is baked in at plan time since no extraction API key is reachable from a static page. A small hand-rolled force-directed layout (simple Euler integration over spring/repulsion forces, maybe 40 lines of vanilla JS, no D3 or vis-network) positions nodes in an SVG canvas and is recomputed every animation frame. On load the full graph (all turns applied) renders immediately so the page demonstrates itself with no clicks; a #timeline range input scrubs the turn index from 0 to 24, showing/hiding nodes and edges according to which turn introduced them, with the transcript list scrolling and highlighting in sync; a #replay-btn snaps the timeline back to 0 so a visitor can watch the graph build itself from empty.

The source post

Scoring

Pick

surprise3
demonstrability4
self_containedness5
honesty4

Graphiti's pitch is that agent memory should be a connected graph, not a scrollback buffer. That's a claim you can actually render: take an agent transcript, extract entities and the relationships asserted between them turn by turn, and lay it out as a graph that grows as you scrub through the session. Everything needed is inlineable text (sample transcripts) and client-side extraction logic, so it runs with no account, no key, and no backend call, and a stranger can see the graph build itself within seconds of loading the page. The other five candidates are a runtime, a model drop, a dev-tooling platform, a native binary, and a crypto-gated app builder, none of which reduce to a single self-contained page.

source: https://x.com/thegreatest_sv/status/2107489054249861141

Review

shipped5
honest4
worth_it3
efficient5

mean 4.25/5

No change: the gate passed first try with no repairs, NOTES.md raises no omissions or objections, and the one notable wrinkle (pick.json's one-liner promised 'paste or load a sample transcript' while plan.json correctly scoped out live extraction as infeasible for a static page) was caught and resolved at plan time at zero cost — one instance isn't evidence of a repeatable pick-stage failure, it's weather.

Cost

total$0.1328
xai$0.1328

metered APIs only, summed across every attempt at this project; Claude and Codex run on flat-rate subscriptions and have no marginal cost per night

What it looked at

@Lokiislive_ethpassed on

Helix**: Open-source vendor-agnostic agentic runtime with OAuth + MCP support; fully runnable local agent framework.

https://x.com/Lokiislive_eth/status/2107373740728488074

It's a local agent runtime/framework meant to be installed and run, not something that compresses into one deployable page.

@k2sbhaipassed on

Exo Free** (OpenCode): New stealth model with 1M context, 131K output, text+image input and high reasoning, 100% free to try at opencode.ai.

https://x.com/k2sbhai/status/2107691740199313604

It's a stealth model announcement; demonstrating it would mean calling a third-party model API we don't hold a key for.

@avynsrcpassed on

Overmind**: Fully open-sourced platform that builds code/agent context graphs and auto-curates fine-tuning data from real traces.

https://x.com/avynsrc/status/2107601766053290403

A context-graph/fine-tuning-data platform that needs real agent traces and pipeline infrastructure, not a single-page artifact.

@inco_aipassed on

Splash** (incoai): Apache-2.0 open-source local inference server (M3+ Mac only) with early demo and brew install.

https://x.com/inco_ai/status/2107981929333366825

A native, M3+-only local inference server installed via brew; not web-deployable or cross-platform.

@zeviodotshpassed on

Zevio AI Harness**: Early public demo of Replit/Lovable-style AI app builder with on-chain compute credits.

https://x.com/zeviodotsh/status/2107982035180490921

Runs on on-chain compute credits, a paid third-party dependency we don't hold and that breaks self-containedness.

@thegreatest_svpicked

Graphiti**: Open-source memory layer that builds connected knowledge graphs from agent activity instead of flat chat logs.

https://x.com/thegreatest_sv/status/2107489054249861141

Gate

passproject directory exists — /Users/artax/code/builds/2026-10-08/project
passno build step needed — static project
passbuild output with index.html — /Users/artax/code/builds/2026-10-08/project
passindex.html is a document — 20081 bytes
passlocal asset references resolve
passpage loads without console errors

Stages

scoutgrok · ok · 14.9s
pickclaude · ok · 44.3s
planclaude · ok · 78.4s
buildcodex · ok · 270.6s
gatelocal · ok · 3.9s
publishlocal · ok · 15.9s
reviewclaude · ok · 66.5s

Notes

Omitted for lack of

None. All planned behavior runs locally. Arbitrary transcript extraction and the other explicitly excluded features remain out of scope.