Skill Creator v5.0 — Complete source: agent skill creation, validation, and empirical eval infrastructure for Claude Code (teaching reference)
Production-grade agent skill creation & validation for AI coding agents By jeremylongshore.com
Now with Anthropic's empirical eval infrastructure: subagent testing, interactive HTML viewer, automated description optimization, benchmark aggregation, blind A/B comparison, and .skill packaging.
Skill: audit-tests
Version: 5.0.0
Author: Jeremy Longshore jeremy@intentsolutions.io
License: MIT
Marketplace Grade: A (99/100)
Compatible With: Claude Code, Codex, OpenClaw
Audit Date: 2026-03-11
Plugin: trading-strategy-backtester
Version: 1.0.0
Author: Intent Solutions IO (jeremy@intentsolutions.ai)
License: MIT
Marketplace: plugins/crypto/trading-strategy-backtester
Audit Date: 2026-03-06
A blueprint for decentralized work coordination with cryptographic proof of every claim, execution, and completion. Built on 5 systems working together, with Dolt as the critical federation primitive.
For decades, work coordination has run on honor systems. A contractor claims they finished a task. You trust them. A platform stores the records. You trust the database. A reviewer says "looks good." You trust their judgment.
Moat is a policy-enforced execution layer for AI agents. It is not an API marketplace, not a permissioning layer bolted onto existing infrastructure, and not a proxy that silently forwards requests.
Moat implements default-deny architecture: every capability (callable action) is inaccessible by default. Agents must hold an active PolicyBundle to execute any capability. Every execution produces three artifacts:
Intent Receipts & Solver Bonds (IRSB) is Ethereum's accountability layer for intent-based transactions and AI agent guardrails.
One-liner: Intents need receipts. Solvers need skin in the game.
ERC-7683 standardizes the intent format—the what and how—but it doesn't answer the critical question: what happens when the solver fails? IRSB fills that gap with an on-chain dispute and slashing framework that provides execution accountability across heterogeneous solvers and protocols.
Real-time AI-powered broadcast intelligence for Atlanta Braves radio. Surfaces AI-generated narratives, player analytics, matchup history, and situational intelligence to announcers and producers during live games — with sub-6-second data latency from MLB's live feed to the broadcast booth.
Three-service monorepo deployed on Google Cloud Platform, designed around a core constraint: zero network dependencies during live broadcast for all cached data.
For: DevOps Engineer Generated: 2026-03-09 Version: v0.9.0 (30 epics shipped)
IntentCAD is a Drawing Intelligence Platform for AEC professionals. Users upload architectural drawings (DXF or PDF), describe what they need in plain English — an edit, a compliance check, a quantity takeoff, a health report — and the platform classifies intent on two axes, selects the right processing pipeline, and delivers structured results. Original files are never modified — every save produces a new file.
A method for building agent skills that are discoverable, maintainable, and production-grade.
This is how we build every skill. It's a synthesis of what actually works after building 1900+ of them — what to include, what to leave out, and how to structure the whole thing so it scales.
More at intentsolutions.io | claudecodeplugins.io