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.

plugins/README.md

@@ -6,7 +6,7 @@ Plugin packages for LibreFang. Plugins extend agent behavior through lifecycle h
 
 ```
 plugins/
-└── echo-memory/
+└── <plugin-name>/
     ├── plugin.toml          # Plugin manifest
     ├── hooks/
     │   ├── ingest.py        # Called on user message
@@ -45,16 +45,20 @@ stdin:  {"type": "after_turn", "agent_id": "...", "messages": [...]}
 stdout: {"type": "ok"}
 ```
 
-## Current Plugins (6)
+## Current Plugins (10)
 
 | Plugin | Hooks | Description |
 |--------|-------|-------------|
 | auto-summarizer | ingest, after_turn | Running conversation summary for long context compression |
+| context-decay | ingest, after_turn | Time-based memory decay with relevance scoring for natural forgetting |
 | conversation-logger | after_turn | Logs conversations to JSONL files for auditing and analytics |
+| episodic-memory | ingest, after_turn | Episode-based conversation segmentation and cross-session recall |
 | guardrails | ingest | Safety filter detecting PII, prompt injection, and credential exposure |
 | keyword-memory | ingest | Extracts keywords and named entities as contextual memories |
 | sentiment-tracker | ingest | Analyzes user sentiment and injects emotional context |
 | todo-tracker | ingest, after_turn | Detects, persists, and recalls action items from conversations |
+| topic-memory | ingest, after_turn | Topic-aware keyword clustering with cross-conversation context recall |
+| user-profile | ingest, after_turn | Persistent user profiling from conversation patterns for personalization |
 
 ## Adding a New Plugin