brute

Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is unreliable across sessions — forgets context, drifts out of scope, claims "done" before tests pass, or starts each session inconsistently — or when creating or assessing AGENTS.md, CLAUDE.md, feature_list.json, init.sh, progress.md, or session-handoff files. Reach for it even if the user never says the word "harness."

Generate a consolidated digest from multiple information sources

Track and report on progress toward defined goals

Review the agent's own recent outputs for quality and accuracy

Generate changelogs from recent commits and merged PRs

Implement features on branches from issue descriptions

Search for and discover community-built Aeon skills

Write long-form articles synthesized from research and analysis

Fetch recent tweets from specific accounts via X.AI API

Scan and summarize recent academic papers from Semantic Scholar

Monitor and summarize activity from tracked subreddits

Aggregate and summarize RSS feed updates

Discovers and ranks tasks from GitHub, GitLab, local files, and custom sources

Coordinate multiple enhancement analyzers in parallel and produce unified report

Unified static analysis — git history, AST symbols, project metadata

Sync documentation with code — find outdated refs, update CHANGELOG, flag stale examples

Autonomously validate that a task is complete and ready to ship — tests, build, and requirement checks

Cross-tool AI consultation — get second opinions from Gemini CLI, Codex CLI, Claude Code, OpenCode, or Copilot CLI

Research any topic online and create comprehensive learning guides with RAG-optimized indexes

Synthesize performance findings into evidence-backed recommendations and decisions

Run sequential performance benchmarks with strict duration rules and baseline management

Clean AI slop from code with certainty-based findings and auto-fixes

Analyze prompts for clarity, structure, examples, and output reliability

Milestone progress tracking and review

Scope deviation detection

Creative ideation with MDA analysis

Design document validation

Statistical analysis and balance verification of game data

Architecture Decision Record documentation

Architectural code review

Technical debt tracking and prioritization

Effort breakdown and estimation

Sprint creation and tracking

Standardized bug documentation

Release pipeline checklist

Auto-generate changelog from git commits

Player-facing release notes generation

Writes, refactors, and evaluates prompts for LLMs generating optimized templates, structured output schemas, evaluation rubrics, and test suites.

Designs production-grade RAG systems with document chunking, embedding generation, vector store configuration, hybrid search pipelines, reranking, and retrieval quality evaluation.

Generates Angular 17+ standalone components, configures advanced routing with lazy loading and guards, implements NgRx state management, applies RxJS patterns, and optimizes bundle performance.