* fix(providers): remove ~anthropic, skip ~ prefixes in sync script
OpenRouter uses ~ prefixes for internal auto-routing aliases (e.g. ~anthropic).
These are not real providers — they already route through openrouter.toml.
The generated ~anthropic.toml was confusing (looked like a stale backup)
and redundant with the existing openrouter provider.
- Delete providers/~anthropic.toml
- Skip provider IDs starting with ~ in sync-pricing.py --create-missing
* fix(providers): remove morph, aider, kwaipilot
- morph: specialized code-editing/patching tool, not a general LLM provider
- aider: CLI meta-tool wrapper (base_url empty), redundant with claude-code/codex-cli/gemini-cli/qwen-code
- kwaipilot: Kwai internal coding assistant routed via OpenRouter, niche
* fix(sync): add morph/aider/kwaipilot to SKIP_PROVIDERS to prevent re-creation
* feat(sync): merge OpenRouter-only providers into openrouter.toml
Instead of generating standalone .toml files that just wrap the OpenRouter
endpoint, merge their models directly into openrouter.toml with the
standard 'openrouter/{provider}/{model}' ID convention.
- Add _build_model_fields() and _model_lines() helpers to deduplicate
model rendering between standalone and merged paths
- Add merge_into_openrouter() that appends new models idempotently
- generate_provider_toml() now only runs for providers in PROVIDER_API
- --create-missing routes OpenRouter-only providers to merge_into_openrouter
* fix(providers): remove 14 OpenRouter-only standalone files
These providers have no direct public API and all route through
openrouter.ai/api/v1. Per the new sync-pricing.py policy, their models
will be merged into openrouter.toml on the next CI run instead of
living in separate files that just wrap the OpenRouter endpoint.
Removed: allenai, deepcogito, essentialai, inclusionai, inflection,
liquid, meituan, nex-agi, nousresearch, prime-intellect, relace,
switchpoint, tngtech, writer
* fix(providers): remove 7 niche providers with no driver support
No dedicated LLM driver code exists for these providers — they rely
purely on OpenAI-compatible passthrough with no special handling.
Removing them reduces registry noise; users can still reach them via
openrouter.toml if needed.
Removed: microsoft, ibm-granite, xiaomi, upstage, inception, aion-labs, arcee-ai
* fix(providers): remove ai21, chutes, venice
All three use ApiFormat::OpenAI with no special handling — pure passthrough.
No registry entry needed; users can reach them via openrouter.toml or by
adding a custom provider.
* docs(providers): rewrite README with full provider catalog and inclusion criteria
- List all 46 providers grouped by category with descriptions
- Document why each provider exists (direct API, unique endpoint, dedicated driver, local, CLI)
- Add inclusion criteria section explaining when to create standalone files vs merging into openrouter.toml
- Document sync script routing logic
- Update model counts: 49→46 providers, 339→232 models
* docs: add comprehensive READMEs for all registry sections + deepinfra provider
- agents/README.md: 32 agents across 7 categories with capability field reference
- channels/README.md: 44 channels across 5 categories with protocol reference table
- hands/README.md: 18 hands across 5 categories with HAND.toml format guide
- mcp/README.md: 33 MCP servers across 5 categories with transport/auth format
- plugins/README.md: 12 plugins with hook protocol documentation
- skills/README.md: 60 skills across 9 categories with SKILL.md format guide
- providers/deepinfra.toml: add DeepInfra serverless inference (5 models)
179 lines
9.4 KiB
Markdown
179 lines
9.4 KiB
Markdown
# Agents Registry
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Agent templates for LibreFang. Each entry is a ready-to-install agent definition with a pre-configured system prompt, model settings, capability declarations, and routing aliases.
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These are the reference agents shipped with the registry. You can install them as-is, override individual fields (model, system_prompt, tools) after installation, or use them as `base` templates inside a Hand.
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## File Format
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Each agent lives in its own subdirectory containing a single `agent.toml`:
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```
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agents/
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├── coder/
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│ └── agent.toml
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├── orchestrator/
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│ └── agent.toml
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└── ...
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```
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### agent.toml format
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```toml
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name = "coder" # must match directory name
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version = "0.4.3-beta3-20260314"
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description = "Expert software engineer. Reads, writes, and analyzes code."
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author = "librefang"
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module = "builtin:chat" # runtime module — builtin:chat for all current agents
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[metadata.routing]
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aliases = ["write code", "fix bug", "implement feature"] # exact activation phrases
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weak_aliases = ["refactor", "patch", "code change"] # keyword hints
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[model]
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provider = "default" # default = use LibreFang's configured primary provider
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model = "default"
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api_key_env = "GEMINI_API_KEY" # optional override: use this key env var
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max_tokens = 8192
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temperature = 0.3
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system_prompt = """You are Coder, an expert software engineer..."""
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[[fallback_models]] # optional: try these providers on failure
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provider = "default"
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model = "default"
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api_key_env = "GROQ_API_KEY"
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[schedule] # optional: continuous or cron activation
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continuous = { check_interval_secs = 120 }
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[resources]
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max_llm_tokens_per_hour = 200000
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max_concurrent_tools = 10
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[capabilities]
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tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch",
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"memory_store", "memory_recall"]
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network = ["*"] # "*" = all, or list specific domains
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memory_read = ["*"]
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memory_write = ["self.*"] # "self.*" = own namespace only
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shell = ["cargo *", "rustc *", "git *", "npm *", "python *"] # shell command allowlist
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agent_spawn = false
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agent_message = [] # agents this agent may message
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[i18n.zh]
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name = "编码工程师"
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description = "资深软件工程师:阅读、编写与分析代码。"
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```
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## Installing and Using Agents
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```bash
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# List all available agent templates
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librefang catalog agents
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# Install an agent from the registry
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librefang agent install coder
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# Install with a custom name
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librefang agent install coder --name my-coder
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# List installed agents
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librefang agent list
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# Send a message to an installed agent
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librefang agent message coder "Implement a binary search function in Rust"
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# Remove an agent
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librefang agent remove my-coder
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```
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Agents can also be used as base templates in a Hand by setting `base = "coder"` in `HAND.toml`.
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## All Agents (33 total)
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### Development
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| Name | Description | Key Tools |
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|------|-------------|-----------|
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| architect | System architect. Designs software architectures, evaluates trade-offs, creates technical specifications. | file_read, file_write, web_search, web_fetch |
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| code-reviewer | Senior code reviewer. Reviews PRs, identifies issues, suggests improvements with production standards. | file_read, shell_exec, web_search |
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| coder | Expert software engineer. Reads, writes, and analyzes code. | file_read, file_write, shell_exec, web_search |
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| debugger | Expert debugger. Traces bugs, analyzes stack traces, performs root cause analysis. | file_read, shell_exec, web_search |
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| devops-lead | DevOps lead. Manages CI/CD, infrastructure, deployments, monitoring, and incident response. | shell_exec, file_read, web_search |
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| ops | DevOps agent. Monitors systems, runs diagnostics, manages deployments. | shell_exec, file_read, web_search |
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| test-engineer | Quality assurance engineer. Designs test strategies, writes tests, validates correctness. | file_read, file_write, shell_exec |
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### Research and Analysis
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| Name | Description | Key Tools |
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|------|-------------|-----------|
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| academic-researcher | Academic research agent. Searches scholarly papers, summarizes findings, and generates literature reviews. | web_search, web_fetch, file_write |
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| analyst | Data analyst. Processes data, generates insights, creates reports. | file_read, web_search, web_fetch |
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| data-scientist | Data scientist. Analyzes datasets, builds models, creates visualizations, performs statistical analysis. | file_read, file_write, shell_exec |
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| researcher | Research agent. Fetches web content and synthesizes information. | web_search, web_fetch, memory_store |
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### Writing and Documentation
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| Name | Description | Key Tools |
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|------|-------------|-----------|
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| doc-writer | Technical writer. Creates documentation, README files, API docs, tutorials, and architecture guides. | file_read, file_write, web_fetch |
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| writer | Content writer. Creates documentation, articles, and technical writing. | file_read, file_write, web_search |
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### Orchestration
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| Name | Description | Key Capabilities |
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|------|-------------|-----------------|
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| orchestrator | Meta-agent that decomposes complex tasks, delegates to specialist agents, and synthesizes results. | agent_spawn, agent_send, agent_list, agent_kill |
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| planner | Project planner. Creates project plans, breaks down epics, estimates effort, identifies risks and dependencies. | file_read, file_write, web_search |
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### Business and Operations
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| Name | Description | Key Tools |
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|------|-------------|-----------|
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| customer-support | Customer support agent for ticket handling, issue resolution, and customer communication. | memory_store, memory_recall, web_search |
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| email-assistant | Email triage, drafting, scheduling, and inbox management agent. | memory_store, memory_recall, file_write |
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| legal-assistant | Legal assistant agent for contract review, legal research, compliance checking, and document drafting. | file_read, file_write, web_search |
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| meeting-assistant | Meeting notes, action items, agenda preparation, and follow-up tracking agent. | memory_store, memory_recall, file_write |
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| recruiter | Recruiting agent for resume screening, candidate outreach, job description writing, and hiring pipeline management. | web_search, file_read, memory_store |
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| sales-assistant | Sales assistant agent for CRM updates, outreach drafting, pipeline management, and deal tracking. | memory_store, memory_recall, web_search |
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| security-auditor | Security specialist. Reviews code for vulnerabilities, checks configurations, performs threat modeling. | file_read, shell_exec, web_search |
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### Personal Productivity
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| Name | Description | Key Tools |
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|------|-------------|-----------|
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| assistant | General-purpose assistant agent. The default agent for everyday tasks, questions, and conversations. | file_read, file_write, web_search, memory_store |
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| health-tracker | Wellness tracking agent for health metrics, medication reminders, fitness goals, and lifestyle habits. | memory_store, memory_recall, file_write |
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| hello-world | A friendly greeting agent that can read files, search the web, and answer everyday questions. | file_read, web_search, web_fetch |
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| home-automation | Smart home control agent for IoT device management, automation rules, and home monitoring. | shell_exec, memory_store, web_fetch |
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| personal-finance | Personal finance agent for budget tracking, expense analysis, savings goals, and financial planning. | file_read, memory_store, web_search |
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| recipe-assistant | Cooking assistant that helps with recipes, meal plans, ingredient substitutions, and portion adjustments. | web_search, memory_recall, file_write |
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| social-media | Social media content creation, scheduling, and engagement strategy agent. | web_fetch, web_search, file_write |
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| translator | Multi-language translation agent for document translation, localization, and cross-cultural communication. | file_read, file_write, web_fetch |
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| travel-planner | Trip planning agent for itinerary creation, booking research, budget estimation, and travel logistics. | web_search, web_fetch, memory_store |
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| tutor | Teaching and explanation agent for learning, tutoring, and educational content creation. | web_search, memory_recall, file_write |
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## Capability Reference
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| Capability field | Values | Effect |
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|-----------------|--------|--------|
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| `tools` | list of tool names | Which built-in tools the agent may invoke |
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| `network` | `["*"]` or domain list | Outbound HTTP domain allowlist |
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| `memory_read` | `["*"]` or namespace list | Which memory namespaces the agent can read |
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| `memory_write` | `["self.*"]` or `["*"]` | Which memory namespaces the agent can write |
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| `shell` | glob patterns | Shell command allowlist (e.g. `"cargo *"`) |
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| `agent_spawn` | `true` / `false` | Whether the agent can spawn child agents |
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| `agent_message` | `["*"]` or agent name list | Which agents this agent may send messages to |
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## Adding a New Agent
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1. Create `agents/<name>/agent.toml` — `name` must match the directory name.
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2. Set `module = "builtin:chat"` unless you have a custom runtime module.
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3. Write a focused `system_prompt` — clear role definition, methodology, and constraints.
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4. Declare only the tools and capabilities the agent actually needs.
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5. Add `[metadata.routing]` aliases so the router can activate the agent by intent.
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6. Run `python scripts/validate.py`.
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7. Submit a PR.
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See [CONTRIBUTING.md](../CONTRIBUTING.md) for the full guide.
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