instruction-workbench

Review planned agent roles, lexical scope overlap, model preferences, and suggested concurrency without starting workers.

Build a reviewed task packet from local source excerpts without a background model call.

Inspect a local Vitest report and retrieve concise diagnostics on demand.

Inspect repeated Bash tool failures without changing tool execution.

Retrieve selected TypeScript definitions and references from an explicit local index, with recorded-input freshness checks.

Prepare a reviewed human-authored handoff with explicit JSON export/import and file text fingerprints.

Appends two or three short follow-up questions after a substantive answer to help users check key facts, probe the reasoning, and notice missing context

19 skills

Easily create custom hooks to prevent unwanted behaviors by analyzing conversation patterns or from explicit instructions. Define rules via simple markdown files.

1 skill · 4 commands · 1 agent · hooks

Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data

9 skills · 9 commands · 11 agents · 1 MCP server

Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.

1 skill

Up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your coding agent's context.

1 MCP server

Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.

2 commands