refactor!: rebrand CCAM to AgentHub

Clean break, no compatibility alias. Renames the product name, the CLI
binary (`ccam` -> `agenthub`), the env var prefix (`CCAM_` ->
`AGENTHUB_`), the Prometheus metric namespace (`ccam_*` ->
`agenthub_*`), the tmux session prefix (`ccam-lane-<id>` ->
`agenthub-lane-<id>`), the per-repo runtime profile directory
(`.ccam/profile` -> `.agenthub/profile`), the lanes state root
(`~/.claude/ccam-lanes` -> `~/.claude/agenthub-lanes`), the bundled
plugins (`plugins/ccam*` -> `plugins/agenthub*`) and their slash
commands (`/ccam-doctor` -> `/agenthub-doctor`, `/ccam:*` ->
`/agenthub:*`).

Because there is no alias, an existing install has to be updated by
hand: rename its `.ccam/profile` directory and any `CCAM_*` variables,
and reinstall the plugin under its new name.

Two other name families are deliberately left alone here, since they are
not just strings: the `Claude-Code-Monitor` repository/marketplace name,
and the `agent-dashboard` npm package plus its `~/.claude/agent-dashboard`
runtime directory, which holds the live database and needs a migration
rather than a rename.

Verified: server 1406/1406, client 459/459, `grep -i ccam` clean across
tracked files, `openapi.yaml` regenerated (95 paths, unchanged count).

plugins/agenthub-insights/skills/optimization-suggest/SKILL.md

@@ -0,0 +1,82 @@
+---
+description: >
+  Suggest concrete optimizations for Claude Code usage based on historical
+  session data. Covers cost reduction, speed improvement, error prevention,
+  and workflow efficiency. Use for data-driven optimization planning.
+---
+
+# Optimization Suggest
+
+Generate data-driven optimization recommendations for Claude Code usage.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- "all" or empty (default: comprehensive optimization scan)
+- "cost" for cost reduction focus
+- "speed" for performance/speed focus
+- "quality" for error reduction focus
+- "efficiency" for workflow efficiency focus
+
+## Procedure
+
+1. **Gather optimization data** from `http://localhost:4820`:
+   - `GET /api/sessions?limit=200` — session history
+   - `GET /api/analytics` — tool and token analytics
+   - `GET /api/pricing/cost` — cost data
+   - `GET /api/pricing` — pricing rules for model comparison
+   - Sample event streams for behavioral analysis
+
+2. **Analyze optimization opportunities**:
+
+   ### 💰 Cost Optimization
+   - **Model downgrade opportunities**: Tasks completed with expensive models that could use cheaper ones
+     - Compare success rates per model per task type
+     - Calculate savings from model substitution
+   - **Cache optimization**: Sessions with low cache hit rates
+     - Identify sessions that could benefit from better prompt caching
+   - **Early termination**: Sessions that ran longer than needed
+     - Detect sessions where useful work completed well before session end
+   - **Compaction reduction**: Sessions hitting context limits
+     - Suggest breaking large tasks into smaller sessions
+
+   ### ⚡ Speed Optimization
+   - **Tool selection**: Faster alternatives for commonly-used tool patterns
+   - **Subagent parallelization**: Tasks that could run in parallel
+   - **Session planning**: Better upfront context to reduce back-and-forth
+   - **Preemptive context loading**: Frequently needed files/context
+
+   ### 🛡 Quality Optimization
+   - **Error prevention**: Common error patterns with preventive measures
+   - **Tool reliability**: Tools with high failure rates and alternatives
+   - **Validation gaps**: Sessions lacking verification steps
+   - **Recovery strategies**: Better error handling patterns
+
+   ### 🔄 Workflow Optimization
+   - **Session sizing**: Optimal session scope based on historical success
+   - **Task decomposition**: Complex sessions that should be split
+   - **Automation candidates**: Repetitive workflows to automate
+   - **Knowledge reuse**: Patterns where previous session context could help
+
+3. **Quantify each recommendation**:
+   - Estimated impact (cost savings $, time savings %, error reduction %)
+   - Implementation effort (low/medium/high)
+   - Confidence level based on data available
+   - Priority score = Impact × Confidence / Effort
+
+## Output Format
+
+Present as a prioritized optimization plan:
+
+| # | Recommendation | Category | Impact | Effort | Priority |
+|---|---------------|----------|--------|--------|----------|
+| 1 | Specific action | 💰/⚡/🛡/🔄 | High | Low | ★★★★★ |
+| 2 | Specific action | ... | ... | ... | ★★★★☆ |
+
+For the top 5 recommendations, include:
+- Detailed explanation with supporting data
+- Step-by-step implementation guide
+- Expected before/after metrics
+- How to measure success