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Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: QuickdrawAchievement: YOLO

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jscraik/README.md

Jamie Scott Craik

AI Delivery Harness Builder, Codex-first engineering that ships, Evidence, review gates, agent workflows

LinkedIn GitHub X

Harness Builder, "Grumpy Old Vet"

British Army veteran | Founder, brAInwav | Codex-first toolmaker

Codex writes the code. I lead, inspect, and make the work accountable. The value is using both strengths properly.

Now (Jun 6, 2026): building synAIpse, Skills SDK, deterministic agent loops, and evidence tooling for teams that want AI coding to ship without losing trust.

By harness, I mean the operating layer around Codex and other coding agents: CLI entrypoints, repo-local guardrails, runtime evidence, review policy, memory, and handoff artifacts that make AI-assisted engineering repeatable.

Last updated: 2026-06-06

Philosophy Mode Focus

What I Build

I build the layer that lets humans use coding agents with more confidence:

  • Agent-ready repos with clear entrypoints, preflight checks, validation gates, and rollback-aware workflows
  • Runtime evidence that separates local test truth from PR state, CI, review threads, tracker status, and merge readiness
  • Capability systems for skills, plugins, prompts, hooks, and review agents that can be validated instead of merely trusted
  • CLI products that make research, architecture, knowledge, and repo intelligence available to humans and agents
  • Local-first memory and narrative tools that preserve intent, decisions, receipts, and context across long-running work

Working Stack

Codex, OpenAI, MCP, TypeScript, Node.js, React, Tauri, Swift, SwiftUI, Python, Bash, macOS, GitHub Actions, CircleCI, CodeRabbit.

TL;DR

Problem: AI coding is fast, but speed is not enough. Teams still need current context, bounded autonomy, repeatable validation, review evidence, and a clean handoff back to humans.

Solution: I build pragmatic Codex-first harnesses: CLIs, instruction systems, skills, evals, review gates, runtime cards, and workflow evidence that turn experiments into dependable engineering operations.

Why it helps: Shorter review loops, fewer vague agent claims, clearer operational defaults, and repos that are easier for both people and agents to pick up safely.

Proof From My Local Repos

Operating problem What I built Repo proof
Agents need a safe next step, not a wall of docs Cockpit-style commands, runtime cards, repo-local gates, and evidence-backed handoff synAIpse / coding-harness private work
Skills and plugins need lifecycle control SDK-style authoring, routing, validation, evals, packaging, sync, and command-surface projections Skills SDK
Long-running agent work needs deterministic state Fresh session loops with file memory, receipts, context snapshots, gates, and review exits ralph-gold
AI-assisted code needs recoverable context Local-first session-to-commit narrative, timelines, and search across the why behind changes trace-narrative
Reviewers and agents need architecture evidence PR impact reports, repo orientation packs, policy validation, and agent handoff artifacts diagram-cli
Research and knowledge tools need agent-safe UX Scriptable CLIs with structured output, explicit policy gates, diagnostics, and safe defaults rSearch, wSearch

Featured Work

Project Why it matters Signal
Agent-Skills Skills SDK for authoring, routing, validating, packaging, and syncing Codex skills and plugins. 5 stars
ralph-gold Deterministic fresh-agent loop with file-based memory, gates, receipts, context snapshots, and review exit rules. 2 stars
trace-narrative Local-first app that links AI sessions, intent, commits, and timelines so teams can recover the why behind code changes. active
diagram-cli Architecture evidence CLI for PR review, repo orientation, agent handoff, policy validation, and Mermaid diagrams. active
rSearch Search, fetch, and download arXiv papers from the terminal. CLI plus TypeScript client. active
wSearch Script-friendly Wikidata REST, SPARQL, and Action API queries from the terminal. active
mKit MCP server boilerplate for Cloudflare Workers. 1 star

Quick Start (Pick One)

# ralph-gold
gh repo clone jscraik/ralph-gold
cd ralph-gold
uv tool install -e .
ralph --help
# rSearch
npm i -g @brainwav/rsearch
rsearch --help
# wSearch
npm i -g @brainwav/wsearch-cli
wsearch --help

More Projects

  • evals - Shared local eval runner for artifact integrity, schema validity, evidence-backed claims, and deterministic scorer verdicts.
  • Design-System - Cross-platform UI workbench and component system for ChatGPT widgets and React apps.
  • unfinished-cemetery - A ritualised archive of abandoned projects — post-mortems for software that died so we could learn what lives.
  • code-archaeology-kit - Privacy-aware git-history intelligence for churn, temporal coupling, abandoned structures, and cleanup targets.

The Search Family

All published under @brainwav on npm:

CLI What it does Install
rSearch arXiv paper search, fetch, download npm i -g @brainwav/rsearch
wSearch Wikidata REST/SPARQL queries npm i -g @brainwav/wsearch-cli

What I'm Doing

  • Shipping synAIpse / coding-harness - a portable AI delivery harness for agent-ready repos, review gates, runtime evidence, and safer PR handoff
  • Building Skills SDK - a governed SDK for Codex skills, plugins, evals, review closeout, and runtime projections
  • Building deterministic agent loops - using ralph-gold to keep task selection, gates, receipts, and exit rules explicit
  • Making context durable - connecting AI sessions, commits, project memory, architecture evidence, and review artifacts
  • Publishing practical CLIs - research, Wikidata, architecture, and repo-intelligence tools with structured output and agent-friendly diagnostics

Work With Me On

AI delivery harnesses - make a repo safer for Codex and other coding agents with entrypoints, gates, evidence, and handoff contracts

Agentic developer workflows - Codex, MCP, review loops, PR automation, runtime cards, and validation policy

Developer tooling and CLIs - research, knowledge, architecture evidence, repo automation, diagnostics, and machine-readable UX

AI governance that actually runs - instructions, drift control, evals, skill lifecycle, review gates, and repeatable workflows that keep human intent visible

Founder/operator advisory - turn messy prototypes into dependable AI-assisted product and engineering systems without losing the point of the work

Learning In Public

I keep an archive of retired experiments at unfinished-cemetery: short post-mortems for software that taught something useful before it was retired.

📬 Connect

LinkedIn X Email

Pinned Loading

  1. rSearch rSearch Public

    Search, fetch, and download arXiv papers from the terminal. CLI + programmatic TypeScript client

    JavaScript

  2. wSearch wSearch Public

    Safe, script-friendly CLI for querying Wikidata via REST, SPARQL, and Action API. Read-only by default with encrypted token storage

    TypeScript

  3. Agent-Skills Agent-Skills Public

    Governed Agent Skills Kit for Codex and AI coding agents: author once, validate quality, expose command handles, and sync runtime projections through ask.

    Python 5 4

  4. ralph-gold ralph-gold Public

    A *Golden Ralph Loop* orchestrator that runs **fresh CLI-agent sessions** (Codex, Claude Code, Copilot) in a deterministic loop until your PRD is complete.

    Python 2 3

  5. code-archaeology-kit code-archaeology-kit Public

    Python

  6. trace-narrative trace-narrative Public

    A new way to discover the narrative, share, and collaborate across GIT and agent traces.

    TypeScript