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
2026-03-21 03:26:11 +09:00
2026-03-21 03:26:11 +09:00
2026-03-21 03:26:11 +09:00

LibreFang Registry

Community-maintained content registry for 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.

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.

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.

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.

[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 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.

# 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:

# 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

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 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.

S
Description
Arka mirror of the LibreFang community content registry — agents, hands, integrations, skills, and provider models. Mirrored from github.com/librefang/librefang-registry.
Readme MIT
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