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Bryan Helmkamp 1e3726b7f3 Add missing data to agent events and cost tracking in pipeline logs 
Enrich three AgentEvent variants with payload data (UserInput.text,
TurnLimitReached.max_turns, SteeringInjected.text) and forward
UserInput/SteeringInjected to the pipeline event stream. Add cost
field to StageUsage (computed from model pricing catalog) and
total_cost to PipelineCompleted (summed from stage outcomes).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Entire-Checkpoint: adb2363c9ec4
2026-02-25 17:17:13 -05:00
..
agent-cli-spec.md docs/specs 2026-02-23 10:17:40 -05:00
attractor-spec.md Add missing data to agent events and cost tracking in pipeline logs 2026-02-25 17:17:13 -05:00
coding-agent-loop-spec.md specs 2026-02-19 13:41:55 -04:00
README.md Rename coding-agent-loop crate to agent 2026-02-23 09:17:48 -05:00
unified-llm-spec.md Fix model alias resolution and invalid gpt-5.2-mini model ID 2026-02-20 14:01:30 -04:00

README.md

Attractor

This repository contains NLSpecs to build your own version of Attractor to create your own software factory.

Although bringing your own agentic loop and unified LLM SDK is not required to build your own Attractor, we highly recommend controlling the stack so you have a strong foundation.

Specs

Building Attractor

Supply the following prompt to a modern coding agent (Claude Code, Codex, OpenCode, Amp, Cursor, etc):

codeagent> Implement Attractor as described by https://factory.strongdm.ai/

Terminology

  • NLSpec (Natural Language Spec): a human-readable spec intended to be directly usable by coding agents to implement/validate behavior.