Borrowing it
Nothing to install: this file belongs to greyhaven-ai/sygaldry. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/greyhaven-ai/sygaldry/main/CLAUDE.mdgit clone --depth 1 https://github.com/greyhaven-ai/sygaldryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/greyhaven-ai/sygaldry/claude-md)<a href="https://agentmods.dev/instructions/greyhaven-ai/sygaldry/claude-md"><img src="https://agentmods.dev/badge/instructions/greyhaven-ai/sygaldry/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/greyhaven-ai/sygaldry/claude-md"><img src="https://agentmods.dev/badge/instructions/greyhaven-ai/sygaldry/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.03531 | $0.03531 |
| Opus 5 | $0.01766 | $0.01766 |
| Sonnet 5 | $0.00706 | $0.00706 |
| Haiku 4.5 | $0.00353 | $0.00353 |
Grade A, and why
sygaldry CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to sygaldry AGENTS.md — 133 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sygaldry Development Context
Project Overview
This is a Sygaldry AI framework project that provides reusable components for LLM-powered applications.
Technical Stack
- Language: Python 3.12+
- LLM Framework: Mirascope v2.0.0-alpha.1
- Data Validation: Pydantic
- Component System: Sygaldry Registry
- Observability: Lilypad (optional)
Development Principles
Mirascope v2 Best Practices
- Functional Prompts: Functions return formatted prompt strings (f-strings) instead of using
@prompt_templatedecorators - Format Models: Use
format=parameter (replacesresponse_model=) for structured LLM outputs - Provider Specification: Use full provider syntax (e.g.,
provider="openai:completions") - Model ID: Use
model_id=parameter (replacesmodel=) - Function-Based Tools: Use
@llm.tooldecorated functions instead ofBaseToolclasses - Async Patterns: Continue using
async deffor all LLM calls and tools - Multi-Provider: Support OpenAI, Anthropic, Google, etc.
- Error Handling: Implement comprehensive validation and error recovery
Component Architecture
- Each component has a
component.jsonmanifest - Components can depend on other registry components
- Include comprehensive documentation and examples
- Follow semantic versioning
Code Quality Standards
- Type hints for all function parameters and returns
- Google-style docstrings
- Comprehensive unit tests
- PEP 8 code formatting
- Proper logging and error handling
Available Components
- text_summarization_agent (agent): Advanced text summarization agent using chain-of-thought reasoning, few-shot learning, and iterative refinement. Supports multiple styles (technical, executive, simple, academic, journalistic) and progressive summarization with validation.
- multi_source_news_verification (agent): Advanced multi-source news verification agent with comprehensive fact-checking tools including academic search, government data verification, social media verification, and expert source validation for combating misinformation
- multi_agent_coordinator (agent): Orchestrates multiple specialized agents to solve complex tasks through intelligent task decomposition, agent selection, and result synthesis
- recruiting_assistant_agent (agent): Recruiting assistant for finding qualified candidates using Exa websets. Helps with technical recruiting, sales hiring, and executive search.
- game_theory_analysis (agent): Analyzes complex strategic situations using game theory principles, identifying equilibria, predicting outcomes, and providing actionable recommendations
- enhanced_knowledge_graph_agent (agent): Enhanced knowledge graph extraction using advanced prompt engineering. Features meta-reasoning for strategy planning, chain-of-thought entity extraction with detailed reasoning, multi-pass relationship detection, and self-consistency validation for high-accuracy results.
- document_segmentation_agent (agent): Agent for intelligently segmenting documents into logical parts. Supports multiple strategies including semantic, structural, hybrid, and fixed-size segmentation. Features document structure analysis, segment summarization, and optimized chunking for vector embeddings.
- knowledge_graph_agent (agent): Agent for extracting structured knowledge from text by identifying entities and their relationships. Builds comprehensive knowledge graph representations with support for hierarchical relationships, graph enrichment, and visualization-ready outputs.
- prompt_engineering_optimizer (agent): Advanced prompt optimization agent that analyzes, generates variants, performs A/B testing, and delivers production-ready optimized prompts with comprehensive documentation
- academic_research_agent (agent): Academic research agent for finding research papers using Exa websets. Perfect for academics, researchers, and anyone needing to discover scholarly publications.
- game_playing_catan (agent): Multi-model turn-based Settlers of Catan game agent supporting AI vs AI, human vs AI, or mixed gameplay with resource management, trading, and strategic building
- research_assistant_agent (agent): AI-powered research agent that conducts comprehensive research using Exa search
- pii_scrubbing_agent (agent): Agent for detecting and removing Personally Identifiable Information (PII) from text. Combines regex patterns and LLM analysis for comprehensive PII detection. Supports multiple scrubbing methods including masking, redaction, generalization, and synthetic data replacement.
- dataset_builder_agent (agent): AI-powered dataset builder that creates curated data collections using Exa Websets with custom criteria and enrichments
- dnd_game_master (agent): A comprehensive D&D 5e game master agent with full rules enforcement and persistent campaign state. Features SQLite-based state persistence for multi-session campaigns, fair dice rolling with modifiers, complete D&D 5e API integration, multi-model orchestration, turn-based combat with positioning, spell slot tracking, condition management, death saves, XP/leveling, exhaustion, skill proficiencies, inventory management, and dynamic roleplay with human-in-the-loop support.
- multi_platform_social_media_manager (agent): Enhanced multi-platform social media campaign manager with trend analysis, engagement prediction, and real-time adaptation capabilities for comprehensive campaign orchestration
- decision_quality_assessor (agent): Comprehensive decision quality assessment agent that analyzes context, evaluates alternatives, detects cognitive biases, and provides actionable recommendations for better decision-making
- sales_intelligence_agent (agent): Sales intelligence agent for finding targeted business contacts and companies using Exa websets. Perfect for sales prospecting, lead generation, and market intelligence.
- market_intelligence_agent (agent): Market intelligence agent for tracking investment opportunities and market trends using Exa websets. Perfect for VCs, analysts, and business development professionals.
- web_search_agent (agent): Unified web search agent supporting multiple providers (DuckDuckGo, Qwant, Exa, Nimble) with configurable search strategies. Features privacy-focused, AI-powered semantic search, structured data extraction, comprehensive, and auto-selection modes.
- game_playing_diplomacy (agent): Multi-model turn-based Diplomacy game agent supporting AI vs AI, human vs AI, or mixed gameplay with sophisticated diplomatic negotiation and strategic planning
- hallucination_detector_agent (agent): AI-powered hallucination detection agent that verifies factual claims using Exa search
- dynamic_learning_path (agent): Generates personalized, adaptive learning paths based on individual skills, goals, and learning preferences with comprehensive resource curation
- sourcing_assistant_agent (agent): Sourcing assistant for finding suppliers, manufacturers, and solutions using Exa websets. Perfect for procurement, supply chain management, and technology sourcing.
- code_generation_execution_agent (agent): Agent for generating and safely executing Python code. Analyzes code for safety, supports multiple safety levels, and provides recommendations for improvement. Features sandboxed execution environment and comprehensive code analysis.
- contract_analysis_agent (agent): Legal document analysis agent for identifying risks, obligations, and key terms in contracts. Provides comprehensive contract review with clause categorization, risk assessment, and actionable recommendations.
- financial_statement_analyzer (agent): Analyzes financial reports, calculates ratios, identifies trends, and provides investment insights with comprehensive ratio analysis and recommendations.
- sentiment_analysis_agent (agent): Multi-dimensional sentiment analysis with emotion detection, aspect-based analysis, and intensity assessment. Analyzes text for overall sentiment, polarity, subjectivity, emotions, and aspect-level sentiments.
- code_review_agent (agent): Automated code review with security vulnerability detection, best practice enforcement, and refactoring suggestions for clean, maintainable code.
- bug_triage_agent (agent): Bug report analysis and classification agent. Analyzes bug reports, classifies severity and priority, identifies root causes, suggests reproduction steps, and recommends fixes.
- task_prioritization_agent (agent): Task prioritization agent using Eisenhower matrix to assess urgency, importance, effort, and impact. Provides optimal task ordering, time allocation, and strategic recommendations for maximum productivity.
- content_moderation_agent (agent): Content moderation agent that detects harmful content, hate speech, misinformation, and spam. Classifies severity and recommends moderation actions.
- customer_support_agent (agent): Multi-turn conversational customer support agent with ticket classification, sentiment analysis, urgency detection, and response generation. Handles technical issues, billing, account access, and feature requests.
- github_issues (tool): GitHub Issues management tool for searching, creating, and updating issues via the GitHub REST API. Integrates with bug triage, code review, and task prioritization agents.
- static_analysis_tool (tool): Python static analysis tool running pylint, flake8, mypy, bandit, and semgrep. Provides code quality checks, type checking, and security vulnerability detection with structured results.
- sec_edgar (tool): SEC EDGAR filing retrieval tool for accessing 10-K, 10-Q, and 8-K filings. Fetches company information, recent filings, and parses basic financial data from the SEC database.
- helpdesk_integration (tool): Zendesk helpdesk integration tool for managing support tickets. Search, create, update tickets and comments via the Zendesk API v2.
- docx_search_tool (tool): Microsoft Word document search and content extraction tool with advanced text search, regex support, and metadata extraction
- directory_search_tool (tool): Advanced file system navigation and search tool with pattern matching, content search, and filtering capabilities
- sqlalchemy_db (tool): SQLAlchemy ORM tool for advanced database operations and agent state management
- firecrawl_scrape_tool (tool): Firecrawl-powered web scraping tool that extracts clean, structured content from websites. Handles JavaScript-rendered pages and provides multiple output formats including Markdown, HTML, and screenshots.
- git_repo_search_tool (tool): Git repository search tool for searching code, files, and commits in both local Git repositories and GitHub. Supports pattern matching, file filtering, and commit history search.
- code_interpreter_tool (tool): Safe Python code execution tool with sandboxing, timeout controls, and variable capture
- pg_search_tool (tool): PostgreSQL database search and query tool with full-text search, connection pooling, and schema introspection
- dice_roller (tool): A fair and transparent dice rolling tool for tabletop RPGs. Supports all standard dice types (d4-d100), modifiers, advantage/disadvantage, and provides detailed roll results with timestamps.
- mdx_search_tool (tool): MDX documentation search tool with JSX component parsing, frontmatter support, and section extraction
- csv_search_tool (tool): CSV search tool for searching and filtering structured data within CSV files. Supports column-specific searches, data filtering, and both exact and fuzzy matching capabilities.
- code_docs_search_tool (tool): Technical documentation search tool for API docs, README files, code comments, docstrings, and code examples
- json_search_tool (tool): JSON search tool for searching and querying within JSON files and data structures. Supports JSONPath expressions, fuzzy matching, and searching in both keys and values.
- pdf_search_tool (tool): PDF search tool that enables searching for text within PDF documents using fuzzy matching. Extracts text from PDFs and provides context-aware search results with page numbers and match scores.
- exa_websets_tool (tool): Advanced web data collection tools using Exa Websets. Create curated collections of web data with search criteria and structured enrichments for building datasets.
- dnd_5e_api (tool): A comprehensive tool for accessing official D&D 5th Edition content via the D&D 5e API. Provides detailed information about spells, classes, monsters, equipment, races, feats, skills, conditions, magic items, and more. Includes advanced search with filters and support for all SRD content types.
- url_content_parser_tool (tool): URL content parsing tool that extracts clean text content from web pages. Removes scripts, styles, and other noise to provide readable text content.
- sqlite_db (tool): SQLite database tool for persistent agent state storage
- nimble_search_tool (tool): Multi-API search tool using Nimble's Web, SERP, and Maps APIs for comprehensive search capabilities
- qwant_search_tool (tool): Privacy-focused web search tools using Qwant search engine. Provides structured search results with no user tracking, using unified models compatible with other search providers.
- duckduckgo_search_tool (tool): DuckDuckGo web search tools with clean, structured results. Provides comprehensive search coverage using the duckduckgo-search library.
- exa_search_tools (tool): AI-powered search tools using Exa. Features neural search, direct Q&A, and similarity search with advanced filtering and relevance scoring.
- youtube_video_search_tool (tool): YouTube video search and transcript extraction tool for content analysis and research
- xml_search_tool (tool): XML data processing tool with XPath queries, namespace support, validation, and advanced search capabilities
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 198 lines · 3,531 tokens per session scan A 85669251db02
sygaldry CLAUDE.md is an instructions file published in the GitHub repository greyhaven-ai/sygaldry (11 stars, last pushed 4mo ago), licensed MIT. It adds 3,531 tokens to every session, about $0.0177 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to sygaldry AGENTS.md, differing in 133 lines, and is treated as a copy.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.