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librefang-registry/README.md
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Evan d1cab3e33a feat: context engine plugins, scaffolding, and pricing fixes (#6)
* feat: add 4 context engine plugins

- topic-memory: keyword clustering for topic-aware memory recall
- episodic-memory: conversation segmentation and cross-session recall
- user-profile: persistent user profiling from conversation patterns
- context-decay: time-based memory decay with reinforcement dynamics

All plugins use the ingest/after_turn hook protocol with stdin/stdout JSON.

* chore: add plugin scaffolding, update docs and templates

- Add plugin.toml template with {{NAME}} placeholder
- Add new-plugin Makefile target with hooks/ scaffolding
- Update plugins/README.md with all 10 plugins
- Update README.md stats (10 plugins, 220+ models)
- Add Plugin checkbox and checklist to PR template
- Add Plugin to issue template content type dropdown
- Fix CONTRIBUTING.md: last_verified is recommended, not required

* fix: correct model pricing and remove deprecated entries

- openrouter/gemma-2-9b-it: fix pricing from 0.0 to 0.03/0.09 per M tokens
  (free variant correctly stays at 0.0)
- github-copilot: remove deprecated copilot/gpt-4 model entry
  (GPT-4 retired in favor of GPT-4o for Copilot)

* docs: annotate kimi-coding as membership-gated

Kimi Code CLI uses quota-based membership model (not per-token billing).
Free tier has limited weekly requests; underlying model is K2.5.
Pricing kept at 0.0 consistent with other subscription providers
(chatgpt, github-copilot) but with explanatory comments.

* style: fix trailing newline in github-copilot.toml

* fix: correct Moonshot/Kimi model pricing from official sources

All 5 models had incorrect pricing:
- moonshot-v1-8k: 0.10/0.10 → 0.20/2.00
- moonshot-v1-32k: 0.30/0.30 → 1.00/3.00
- moonshot-v1-128k: 0.80/0.80 → 2.00/5.00
- kimi-k2: 2.00/8.00 → 0.60/2.50
- kimi-k2.5: 2.00/8.00 → 0.45/2.20

Sources: platform.moonshot.ai/docs/pricing/chat, costgoat.com, getmaxim.ai

* feat: add MiniMax M2.7 and M2.7-highspeed models

Released 2026-03-18, MiniMax's latest flagship text model.
10B activated params, 200K context, 128K output, tool use, streaming.
Pricing: $0.30/$1.20 per M tokens (input/output).

Added to both international (minimax.io) and China (minimaxi.com) providers.
2026-03-21 03:36:32 +09:00

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Markdown

# LibreFang Registry
Community-maintained content registry for [LibreFang](https://github.com/librefang/librefang) -- the open-source Agent Operating System.
This repository is the single source of truth for all installable content definitions. Anyone can submit a PR to add new agents, hands, integrations, skills, or provider models -- no changes to the LibreFang binary required.
## Structure
```
librefang-registry/
├── agents/ # Agent definitions (TOML manifests)
│ ├── hello-world/agent.toml
│ ├── researcher/agent.toml
│ └── ... (33 agents)
├── hands/ # Hand definitions (TOML + docs)
│ ├── browser/HAND.toml
│ ├── trader/HAND.toml
│ └── ... (14 hands)
├── integrations/ # MCP server integration templates
│ ├── github.toml
│ ├── slack.toml
│ └── ... (25 integrations)
├── skills/ # Reusable skill definitions
│ ├── custom-skill-prompt/skill.toml
│ └── custom-skill-python/
├── providers/ # LLM provider & model metadata
│ ├── anthropic.toml
│ ├── openai.toml
│ └── ... (46 providers, 190+ models)
├── plugins/ # Plugin packages (10 plugins)
├── aliases.toml # Global model alias mappings
├── schema.toml # Provider/model schema reference
├── scripts/
│ └── validate.py # Validation script
├── CONTRIBUTING.md
└── LICENSE # MIT
```
## Content Types
### Agents
Agent definitions in `agents/<name>/agent.toml` describe autonomous agents with their model config, tools, capabilities, and routing aliases.
```toml
name = "hello-world"
description = "A friendly greeting agent"
module = "builtin:chat"
[model]
provider = "default"
model = "default"
system_prompt = "You are a helpful assistant."
[capabilities]
tools = ["web_search", "file_read"]
```
### Hands
Hands in `hands/<name>/HAND.toml` are higher-level application bundles -- the user-facing "apps" in LibreFang. Each hand bundles an agent config, tools, settings, dashboard metrics, and dependency requirements.
```toml
id = "browser"
name = "Browser Hand"
category = "productivity"
tools = ["browser_navigate", "browser_click", "browser_type"]
[agent]
name = "browser-hand"
module = "builtin:chat"
system_prompt = "You are an autonomous web browser agent..."
[[settings]]
key = "headless"
setting_type = "toggle"
default = "true"
```
### Integrations
Integration templates in `integrations/<name>.toml` define MCP server connections (GitHub, Slack, databases, etc.) with transport config, required env vars, and setup instructions.
```toml
id = "github"
name = "GitHub"
category = "devtools"
[transport]
type = "stdio"
command = "npx"
args = ["-y", "@modelcontextprotocol/server-github"]
[[required_env]]
name = "GITHUB_PERSONAL_ACCESS_TOKEN"
is_secret = true
```
### Skills
Skills in `skills/<name>/skill.toml` are reusable prompt templates or Python scripts that agents can invoke.
```toml
[skill]
name = "meeting-agenda"
description = "Generate a structured meeting agenda"
[runtime]
type = "promptonly"
[prompt]
template = "Create a meeting agenda for: {{topic}}"
```
### Providers
Provider files in `providers/<name>.toml` define LLM providers and their models with pricing, context windows, and capability flags. See [schema.toml](schema.toml) for the full field reference.
## How LibreFang Uses This Registry
LibreFang ships with built-in content compiled into the binary. This repository serves as the upstream source for updates and community contributions.
```bash
# Update all registry content
librefang catalog update
# Install a specific hand
librefang hand install browser
# Install a specific integration
librefang integration install github
```
### Custom Local Content
You can also create custom content locally without submitting a PR:
```bash
# Create a custom agent
mkdir -p ~/.librefang/agents/my-agent
# Edit ~/.librefang/agents/my-agent/agent.toml
# Add custom models to your config
# ~/.librefang/model_catalog.toml
```
## Validation
```bash
python scripts/validate.py
```
This validates all provider TOML files for correctness: required fields, valid tiers, non-negative costs, no duplicate IDs.
## How to Contribute
1. Fork this repository
2. Add or edit content in the appropriate directory
3. Run validation: `python scripts/validate.py`
4. Submit a Pull Request
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed instructions for each content type.
## Current Stats
| Type | Count |
|------|-------|
| Agents | 33 |
| Hands | 14 |
| Integrations | 25 |
| Skills | 2 |
| Plugins | 10 |
| Providers | 46 |
| Models | 220+ |
| Aliases | 80+ |
## License
MIT License. See [LICENSE](LICENSE).