skill-synthesis

Compose multiple installed skills into one coordinated execution stack with ordered packets, minimal context load, and deterministic handoff artifacts. Use when tasks span multiple domains (for exampl

SKILL.md

GitHub

Skill Synthesis

Overview

Use this skill to fuse multiple installed skills into one execution loop with clear ordering, packet boundaries, and artifacts.

This skill is also the preferred bridge when work spans:

  • repo code and canonical docs
  • Notion exports and live Notion pages
  • Obsidian vault notes
  • local research/foundation texts

It should treat those sources as layered evidence, not one flat corpus.

Quick Start

  1. Build a stack from a task prompt.
python C:\Users\issda\.codex\skills\skill-synthesis\scripts\compose_skill_stack.py --task "Build gamma funnels and deploy" --top 8
  1. Run the resulting packets in order from highest leverage to lowest risk.

Workflow

1) Select Minimal Stack

  • Pick one primary skill (owns outcome).
  • Pick up to five support skills (execution lanes).
  • Do not load the whole skill catalog unless explicitly requested.
  • If the task spans repo + Notion + Obsidian + local notes, prefer a foundation map pass before implementation.

2) Build Ordered Packets

  • Packet A: foundation-source scan
  • Packet B: canonicality split (canonical, operational, exploratory, evidence, historical)
  • Packet C: implementation/modeling
  • Packet D: validation/smoke
  • Packet E: publish/deploy
  • Packet F: evidence + vault notes

3) Turing / Local-Rule Conversion Rule

When a task sounds infinite, metaphor-heavy, or underdefined, convert it into a finite engineering packet instead of debating abstractions.

Required conversion fields:

  • state space
  • initial state
  • local update rule
  • monitored quantity
  • validation harness
  • lane tag: facts, tested-results, or theories-untested

Use this for theory-to-runtime bridges such as ternary governance, phi-lifts, Turing-tape style local rules, or manifold overlays.

4) Execute with Context Discipline

  • Keep live context to only the active packet.
  • Move long notes to artifacts or vault docs.
  • Keep source links and proofs in packet output.
  • When foundation texts disagree, code-first canonical surfaces win unless the task is explicitly archival or patent-history oriented.

5) Output Contract

  • stack plan JSON
  • ordered packet list
  • execution report (what ran, what passed, what is blocked)
  • evidence paths for each packet

Built-in Stack Profiles

hydra-library-wing

  • hydra-clawbot-synthesis
  • aetherbrowser-arxiv-nav
  • aetherbrowser-github-nav
  • hugging-face-model-trainer
  • notion

Use for deep research + dataset handoff + multi-agent synthesis.

revenue-gamma-funnel

  • living-codex-browser-builder
  • article-posting-ops
  • scbe-shopify-money-flow
  • aetherbrowser-shopify-nav
  • vercel-deploy

Use for landing pages, conversion flow, and web deployment.

platform-release

  • development-flow-loop
  • playwright
  • scbe-connector-health-check
  • vercel-deploy

Use for implementation -> smoke -> deploy.

foundation-magma-map

  • scbe-codebase-orienter
  • obsidian-vault-ops
  • notion-research-documentation
  • scbe-system-engine
  • agent-handoff-packager

Use for turning repo docs, Notion exports, Obsidian, and local research texts into one authority map.

ternary-turing-bridge

  • scbe-experimental-research-safe-integration
  • development-flow-loop
  • scbe-context-full-test-suite
  • obsidian-vault-ops
  • notion-research-documentation

Use for converting ternary / Turing / manifold theory into finite local-rule experiments, docs, and bounded validation lanes.

docs-funnel-evidence

  • scbe-github-pages-funnel-builder
  • development-flow-loop
  • playwright
  • obsidian-vault-ops

Use for taking a validated system surface and turning it into a linked GitHub Pages funnel with evidence trails.

security-corpus-prism

  • notion-research-documentation
  • scbe-experimental-research-safe-integration
  • hugging-face-datasets
  • development-flow-loop
  • obsidian-vault-ops

Use for turning primary security/framework sources into structured UM and DR training packets such as framework summaries, control crosswalks, diagram packets, working-vs-broken examples, attack-to-control maps, and debate/conclusion packets.

github-gitlab-pond-meridian-flush

  • scbe-gitlab-pond-integration
  • gh-fix-ci
  • gh-address-comments
  • scbe-github-sweep-sorter
  • scbe-github-systems
  • aetherbrowser-github-nav

Use for keeping cross-pond flows unblocked: quick pond flush, then PR/CI triage, then comment handling, then sweep routing.

Rules

  • Favor official docs and primary sources for unstable facts.
  • Keep stack size small unless user explicitly asks for full-spectrum mode.
  • Prefer deterministic scripts and repeatable packets over ad-hoc chat instructions.
  • Record evidence paths for every packet.
  • Treat foundation mapping as a first-class packet, not a side note, when system ontology is in question.

Resources

scripts/

  • compose_skill_stack.py: Generate ranked skill stacks and packet plans from a task description.

references/

  • stack-profiles.md: Reusable profile templates and packet recipes.