Overview

We use two layers to build a profile to guide AI agents on your behalf.

1. Existential Layer: Asks questions to your introspective content like journals to uncover drivers and aspirations.
2. Operational Layer: Processes your public content, work output, emails, social posts to see how you carryout actions.

These layers build on one another to create datasets to inform choices and scaffold actions with existential underpinnings.

Basically, we run systems that will explain why you choose things to AI.

This internal monologue annotates dataset with reasoning traces to introspect better and explain to AI models why/how it should do something.

Nix Flake Outputs

Skills are unified under workspaces/skills and exposed in two downstream skill shapes, alongside translation-layer and alignment outputs:

Output	Purpose
lib.artifacts.skills.files.<skill-name>	Flat skill content keyed by skill name
lib.artifacts.skills.names	Available skill names
lib.artifacts.skills.categorized	Categorized skill tree shaped as <category>/<skill>/...
lib.artifacts.alignment.spec	Generated alignment spec
lib.artifacts.alignment.translationLayer	Generated translation-layer orchestrator soul (SOUL.md)
lib.artifacts.alignment.interactionPosture	Generated interaction posture (INTERACTION_POSTURE.md)
lib.artifacts.operational.toolSpecs.{memory,tasks}	Operational tool specs

Downstream Usage

{ pkgs, inputs, ... }:

let
  cognitive = inputs.cognitive-assistant;
  system = pkgs.stdenv.hostPlatform.system;
  artifacts = cognitive.lib.artifacts;
  operational = artifacts.operational;
  alignment = artifacts.alignment;
in
{
  # Categorized Hermes-style skill tree: <category>/<skill>/SKILL.md.
  environment.etc."hermes/skills".source = artifacts.skills.categorized;

  # Operational profile tool specs.
  programs.opencode.tools = {
    memory = builtins.readFile operational.toolSpecs.memory;
    tasks = builtins.readFile operational.toolSpecs.tasks;

  };

  # Generated alignment spec.
  environment.sessionVariables.ALIGNMENT_SPEC = "${alignment.spec}";
}

Regeneration Workflow

The repo runs as one unified pipeline parameterized by a layer profile (existential or operational) for profile-specific build steps.

# Existential profile
python -m core --profile existential ask-questions
python -m core --profile existential build-prompts
python -m core --profile existential build-skills

# Operational profile
python -m core --profile operational ingest-corpus
python -m core --profile operational ask-questions
python -m core --profile operational build-prompts
python -m core --profile operational build-skills
python -m core --profile operational build-tool-specs

# Cross-profile / shared commands
python -m core enhance-skill
python -m core build-translation-layer
python -m core build-alignment-spec

Question answering retrieves from configured QMD collections. Existential uses Journal and Personal; operational uses Base, Consulting, and Customers. Raw source notes are not copied into this repository.

build-skills reads the active profile's latest human_profile*.md, but writes to the unified skill store. Cross-system consumers should read skills only from workspaces/skills or lib.artifacts.skills.*, not from profile artifact directories.

Generated canonical skills land at: workspaces/skills/<profile>/<skill-name>/SKILL.md

build-translation-layer reads both profile artifacts and produces the orchestrator translation layer: the interaction posture inference and the durable orchestrator soul. Outputs land at: workspaces/alignment/artifacts/INTERACTION_POSTURE.md workspaces/alignment/artifacts/SOUL.md

workspaces/skills/<profile>/<skill-name>/SKILL.md
workspaces/alignment/artifacts/INTERACTION_POSTURE.md
workspaces/alignment/artifacts/SOUL.md

Use profile folders when the generator does not yet have a better stable category. Do not write generated skills into opaque folders like group-1.

Alignment Spec

The alignment command sits above both profiles. It reads unified skills from workspaces/skills and writes a personalized production-readiness checklist.

# Build the spec (requires build-skills to have been run)
python -m core build-alignment-spec

Regenerate the spec whenever skills change. See profiles/alignment/README.md for architecture and details.