Build LLM Tool — Testing skill for Claude Code
Build the LLM chat-history tool app (Ktor + Koog + SQLite) per spec: invoke agents strictly in order, run acceptance checks, report.
How to install Build LLM Tool
Installs to ~/.claude/commands/p1nkyswear-chat-history-harness-build-llm-tool.md
mkdir -p ~/.claude/commands && curl -fsSL https://raw.githubusercontent.com/P1nkySwear/chat-history-harness/HEAD/.claude/commands/build-llm-tool.md -o ~/.claude/commands/p1nkyswear-chat-history-harness-build-llm-tool.md Restart Claude Code, or start a new session, for it to be picked up.
What Build LLM Tool does
description: Build the LLM chat-history tool app (Ktor + Koog + SQLite) per spec: invoke agents strictly in order, run acceptance checks, report allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Agent, Skill, WebFetch, WebSearch argument-hint: "[optional: path to a spec file]"
/build-llm-tool — build the LLM chat-history tool app
You are the **orchestrator**. You do not write application code yourself: you invoke agents sequentially via the **Agent** tool and control their output.
Alternatives in Testing
- Debug — You are tasked with helping debug issues during manual testing or implementation 10k ★
- Agent Skills Spec — A skill is a folder of instructions, scripts, and resources that agents can discover and load dynamically to p 1.9k ★
- Mobile Scan — Quick QA scan of an existing mobile app 107 ★
Full documentation available on GitHub
View Source RepositoryRelated Skills
Phased Engineering Pipeline
Claude Code skill for building software with AI agents: seven roles, vertical-slice phases, deterministic chec
Conversational
Spec a conversational UI — voice assistant, chatbot, AI chat (LLM), or live-agent chat. Modality, persona, int
Autoconst Spec Compliance Claude
Cross-check a Revit model against its written CSI construction spec. Auto-indexes the spec into SQLite, auto-e
Q Validate
Full validation of Spec-Kit-Plus workflow - checks order, artifacts, and detects violations
Ragagentsv1v2
RAG chat agent for your own documents, built in two stages. V1 answers with local models only (hybrid search,
Fix Spec
Apply fixes from a /review-spec report — resolve all FAIL items, re-run review checks, mark spec Approved
Related Agents
QA Documenter
Oracul QA documenter. Writes the release QA pack (test plan, acceptance report, how-to-run) strictly from real
Kotlin
Server-side Kotlin expert (NOT mobile - that is app). Consulted before backend to lay out a Kotlin service - K
Prompt Reviewer Logs
Reads LLM input/output records from any database (Postgres, MongoDB, MySQL, BigQuery, SQLite, etc.) via standa