SEARCH_DIRECTIVES.md — What Versailles Is Hunting For

This document defines the search primitives — the types of things Versailles agents should actively discover, create, and curate. It gives the Scout and other agents clear direction on what to bring in and what to ignore.

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Two Tracks, Two Purposes

Versailles searches for two fundamentally different things:

Track 1: Agent Skills (→ skills/)

What: SKILL.md files that teach agents how to do specific tasks better. Pipeline: Discovered → Bouncer → Evaluator → Evolver (full self-evolution). Goal: Build a library of production-ready, A/B-tested agent instructions that measurably outperform raw Claude.

Track 2: Open Source Projects (→ projects/)

What: GitHub repos, tools, libraries, and frameworks that are useful for agent-powered development and orchestration. Pipeline: Discovered → Vetted → Cataloged (no evolution — projects are external). Goal: Build a curated catalog of best-in-class tools for the agentic ecosystem.

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Skill Search Directives

Priority Skill Categories

These are the kinds of agent skills Versailles should actively seek out and create. Ordered by priority for the owner's needs:

1. Agent Orchestration & Workflow Skills

Skills that make agents better at coordinating multi-agent work, managing swarms, routing between models, and self-organizing.

• Swarm coordination patterns
• Model routing and tier selection
• Task decomposition and delegation
• Agent-to-agent handoff protocols

2. Code Quality & Security Skills

Skills that improve code review, security analysis, and development practices.

• Security vulnerability scanning (OWASP, dependency audit)
• Code review with actionable feedback
• Architecture decision records (ADRs)
• Test generation and TDD patterns

3. Research & Knowledge Synthesis Skills

Skills that make agents better at deep research, knowledge extraction, and connecting ideas across domains.

• Recursive research with progressive deepening
• Source evaluation and credibility scoring
• Knowledge graph construction
• Cross-domain insight synthesis

4. Repository Management Skills

Skills for maintaining, documenting, and evolving repositories autonomously.

• README and documentation generation
• Issue triage and labeling
• PR review and merge decisions
• Changelog and release note generation

5. Prompt Engineering & Self-Improvement Skills

Skills that make agents better at writing prompts, creating other skills, and improving their own instructions.

• Skill authoring (meta-skill)
• Prompt optimization and compression
• Self-evaluation and scoring
• Context window management

Skill Search Queries

When the Scout searches GitHub, use these queries to find skills specifically:

"SKILL.md" in:path                                    # Direct SKILL.md files
"agent skill" in:name,description stars:>10            # Repos packaging agent skills
topic:agent-skills                                     # Tagged with agent-skills topic
"---\nname:" "description:" in:file path:SKILL.md      # YAML frontmatter pattern
org:anthropics path:skills                             # Official Anthropic skills

Skill Creation Directives

When no suitable existing skill is found, the Scout or Researcher should draft a new skill in skills/discovered/. A drafted skill should:

1. Follow the SKILL.md format (see SKILL_SPEC.md)
2. Include at least 3 concrete examples
3. Define clear trigger conditions ("Use when...")
4. Be specific enough to A/B test meaningfully
5. Target one of the priority categories above

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Project Search Directives

Priority Project Categories

These are the kinds of open source projects Versailles should track:

1. Agent Orchestration Frameworks

Multi-agent coordination tools, swarm managers, and workflow engines.

• Example: ruvnet/ruflo (claude-flow) — swarm orchestration with model routing, memory systems, and 60+ agent types
• Example: github/gh-aw — natural language → GitHub Actions compilation

2. MCP Servers & Integrations

Model Context Protocol servers that extend agent capabilities.

• Example: modelcontextprotocol/servers — official MCP reference implementations
• Look for: filesystem, database, API, memory, and search servers

3. AI Development Tools

Tools that improve the AI-powered development workflow.

• Code generation assistants
• Testing frameworks for AI outputs
• Evaluation harnesses and benchmarks
• Prompt management systems

4. Security & Guardrails

Tools that make agent operations safer and more controllable.

• Agent firewalls and network isolation
• Permission management for AI actions
• Audit logging and compliance tools
• Input/output sanitization

5. Knowledge & Memory Systems

Tools for persistent agent memory, knowledge graphs, and retrieval.

• Vector databases and embedding tools
• Knowledge graph builders
• RAG (Retrieval Augmented Generation) frameworks
• Persistent memory servers

Project Search Queries

"multi-agent" orchestration in:name,description stars:>50     # Orchestration tools
"model context protocol" server in:name,description           # MCP servers
claude agent tool in:name,description stars:>20               # Claude ecosystem
"agent framework" in:name,description language:python,typescript stars:>100
topic:mcp-server OR topic:agent-framework                    # Tagged repos

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Owner Preferences (Bespoke Curation)

Versailles is curated for a specific use case. The owner's priorities are:

1. Non-developer operation — Everything must work from GitHub's web UI. Prefer tools with GUI/web interfaces or that integrate with GitHub Actions.
2. Self-building repos — Prioritize tools that enable repositories to update and improve themselves autonomously (like gh-aw).
3. Multi-agent orchestration — The owner uses claude-flow/RuFlo for swarm coordination. Prioritize tools that work with or complement this stack.
4. Progressive disclosure — Prefer tools that load context incrementally rather than dumping everything at once.
5. Security-first — Zero-trust by default. Every external tool is suspect until proven otherwise.

Tools the Owner Already Uses

These are known-good tools in the owner's ecosystem. New discoveries should complement, not duplicate, these:

Tool	Purpose	Repo
RuFlo (claude-flow)	Multi-agent orchestration, swarm management	ruvnet/ruflo
GitHub Agentic Workflows	Natural language → GitHub Actions	github/gh-aw
MCP Filesystem Server	Safe file read/write	modelcontextprotocol/servers
MCP GitHub Server	GitHub API access	modelcontextprotocol/servers
MCP Sequential Thinking	Step-by-step reasoning	modelcontextprotocol/servers
Context7	Library documentation lookup	@upstash/context7-mcp

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How This File Is Used

• Scout workflow reads this file to determine search queries and priorities
• Researcher agent uses the priority categories to focus deep research
• Human operator updates this file to shift priorities as needs change
• Bouncer uses the owner preferences to contextualize security decisions

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Updated: 2026-03-26 | Read by: Scout, Researcher, Bouncer