Results for “agent-to-agent”

Audits a project's agent configuration files, establishes a source-of-truth skills directory, normalizes naming, and generates bridge files to make the workspace consistent across Claude Code, Codex, Grok, and generic Agents.

Generates a comprehensive AGENTS.md file at the repository root to provide AI coding agents with project context, setup commands, development workflows, testing instructions, and code style guidelines.

Uses two independent review agents to verify output quality, requiring both to pass before shipping.

Run multiple AI agents against a product, SDK, or docs site to score setup friction, speed, efficiency, error recovery, and doc quality from a minimal prompt.

Routes requests to design, create, debug, update, or upgrade GitHub Agentic Workflows by loading the appropriate workflow prompt or skill file.

Routes requests to design, create, update, debug, or upgrade GitHub Agentic Workflows by loading the appropriate workflow prompt or skill file.

Create, edit, and verify agent skills using test-driven development to ensure agents follow documented procedures correctly.

Delegates tasks to specialized AI agents running in parallel via the Box0 platform, enabling code review, security checks, research, and documentation.

Converts legacy agent resources such as subagents, commands, and rules into the unified Agent Skills format, with classification, conversion, and verification steps.

Create and maintain GitHub Copilot custom agents in Visual Studio Code with defined roles, tool restrictions, model selection, subagent permissions, and handoffs.

Audits AGENTS.md and CLAUDE.md files for bloat, redundancy, and ineffective rules, then runs A/B evals to prove which instructions are dead weight.

Bootstraps AGENTS.md and CLAUDE.md for AEM 6.5 LTS projects, tailored to project structure and detected add-ons.

Analyzes a codebase to create or improve an AGENTS.md file, capturing conventions, constraints, and rationale that are expensive to rediscover.

Composes ad-hoc teams of AI agents from local markdown personas and dispatches them in parallel on a task, then synthesizes their outputs.

Compact the current conversation into a handoff document for another agent to pick up, including suggested skills and references to existing artifacts.

Compacts the current conversation into a handoff document for another agent to continue the work, saving it to the OS temporary directory.

Research existing tools, libraries, and patterns before writing custom code by invoking a researcher agent.

Routes tasks to specialized agent offices and applies behavioral science frameworks to every output, with confidence tagging and session memory.

Writes or updates a HANDOFF.md document to preserve context for the next agent, including goal, progress, what worked, what didn't, and next steps.

Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.

Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.

Generates a clipboard-ready handoff prompt for another AI agent to investigate or continue a task, with structured context and review instructions.

Provides cross-harness memory for agents by maintaining a local memex and offering commands to query, record, and check status across sessions.

Orchestrates building a new feature end-to-end by delegating research, planning, TDD implementation, review, and gated commit to specialized agents.

Compacts the current conversation into a handoff document for another agent to pick up, referencing existing artifacts by path or URL instead of duplicating them.

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

Scaffolds new agent skills conforming to the Agent Skills specification and dotnet/skills repository conventions, generating SKILL.md files with proper frontmatter and directory structures.

Bridge any skill folder or directory of skill folders to Claude Code, Codex, generic Agents, and Grok using symlinks plus Grok bridge files.

Routes engineering design, delivery, reliability, security, operations, and maintenance prompts to a router skill backed by specialist guidance for multiple AI coding agents.

Debug and optimize AI agents by analyzing reasoning traces, context degradation, tool confusion, instruction drift, repeated task failures, and performance regressions.