OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add RightNow-AI/openfang --skill graphql-expertgit clone --depth 1 https://github.com/RightNow-AI/openfangWrote 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/skills/rightnow-ai/openfang/graphql-expert)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/graphql-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/graphql-expert.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00019 | $0.00613 |
| Opus 5 | $0.00010 | $0.00307 |
| Sonnet 5 | $0.00004 | $0.00123 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
graphql-expert 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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- graphql-expert — 100% identical, 0 lines differ
- graphql-expert — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GraphQL Expert
A backend API architect with deep expertise in GraphQL schema design, resolver implementation, real-time subscriptions, and query performance optimization. This skill provides guidance for building robust, well-typed GraphQL APIs that scale efficiently while maintaining an excellent developer experience for API consumers.
Key Principles
- Design schemas around the domain model, not the database schema; GraphQL types should represent business concepts with clear relationships
- Use input types for mutations and keep query arguments minimal; complex filtering belongs in dedicated input types
- Prevent the N+1 query problem proactively by implementing DataLoader patterns for every resolver that accesses a data source
- Treat the schema as a contract; use deprecation directives before removing fields and version through additive changes rather than breaking ones
- Enforce query complexity limits and depth restrictions at the server level to prevent abusive or accidentally expensive queries
Techniques
- Define types with clear nullability: non-null (String!) for required fields, nullable for fields that may genuinely be absent
- Implement resolvers that return promises and batch data access; use DataLoader to batch and cache database calls within a single request
- Set up subscriptions over WebSocket (graphql-ws protocol) with proper connection lifecycle handling (init, ack, keep-alive, terminate)
- Use fragments to share field selections across queries and reduce duplication in client-side code
- Apply custom directives (@auth, @deprecated, @cacheControl) for cross-cutting concerns like authorization and cache hints
- Implement cursor-based pagination following the Relay connection specification (edges, nodes, pageInfo with hasNextPage and endCursor)
- Structure error responses with extensions field for error codes and machine-readable metadata alongside human-readable messages
Common Patterns
- Schema Federation: Split a monolithic schema into domain-specific subgraphs that compose into a unified supergraph via a gateway, enabling independent team ownership
- Persisted Queries: Hash and store approved queries server-side; clients send only the hash, reducing bandwidth and preventing arbitrary query execution
- Optimistic UI Updates: Design mutations to return the mutated object so clients can update their local cache immediately without a refetch
- Batch Mutations: Accept arrays in input types for bulk operations while returning per-item results with success/failure status for each entry
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.
- 8d ago First seen · 40 lines · 19 tokens per session scan A 54a6ebb60fa3
graphql-expert is a skill published in the GitHub repository RightNow-AI/openfang (18,167 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 19 tokens to every session and 613 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
copilotkit-upgrade
Use when migrating a CopilotKit v1 application to v2 -- updating package imports, replacing deprecated hooks and components, switching from GraphQL runtime to AG-UI protocol runtime, and resolving breaking API changes.
webhook-subscriptions
Create and manage webhook subscriptions for event-driven agent activation. Use when the user wants external services (GitHub, GitLab, Stripe, Linear, PagerDuty, Sentry, or any generic source) to trigger agent runs by POSTing events to a URL.
tool-design
Design and verify tools that AI agents can actually use — for any framework or language (MCP servers, LangChain/LangGraph, function-calling, raw JSON schema; TypeScript, Python, or otherwise). Use when writing a new tool for an agent, reviewing or fixing an existing tool definition, deciding how to split capabilities…
后端编码
A backend coding guide covering web APIs, databases, error handling, logging, and endpoint tests. Backend code runs on servers and handles data and application operations.
软件方案规划
A software planning guide for deciding how a project should be structured and built. It covers architecture, technology choices, modules, interfaces, requirements, and testing.
agent-crdt-synchronizer
Agent skill for crdt-synchronizer - invoke with $agent-crdt-synchronizer.