M21: Token optimization -- reduce API token consumption

[bug-ops]

Problem

Usage analysis shows catastrophic token waste: ~1.9M input tokens vs ~9.8K output (200:1 ratio) with zero cache hits across all requests.

Root Causes

1. No prompt caching -- ClaudeProvider sends system prompt + skills as plain text every request. Anthropic prompt caching API is not used.
2. Tool loop amplification -- each iteration of process_response_native_tools resends the full message history. With 10 iterations, that is 10x the system prompt + history.
3. LLM-based summarization uses primary model -- summarize_tool_output and compact_context make separate Claude API calls.
4. Bloated system prompt -- rebuild_system_prompt injects skills + catalog + environment + tool catalog + MCP prompt + project configs + repo map.

Estimated Impact

Optimization	Token Reduction	Effort
Prompt caching	80-90%	Medium
Local model for summarization	Eliminates extra API calls	Low
Aggressive context pruning	30-50% of history	Low
Usage metrics	Observability	Low

Phases

• M21-P1: Anthropic prompt caching for ClaudeProvider #337 Phase 1: Prompt caching (structured system blocks + anthropic-beta header)
• M21-P2: Local model for tool output summarization #338 Phase 2: Local model for tool output summarization
• M21-P3: Aggressive context pruning in tool loops #339 Phase 3: Aggressive context pruning in tool loops
• M21-P4: Cache usage metrics tracking #340 Phase 4: Cache usage metrics tracking

Architecture

See `.local/plan/m21-token-optimization.md`

Key Files

• `crates/zeph-llm/src/claude.rs`
• `crates/zeph-core/src/agent/streaming.rs`
• `crates/zeph-core/src/agent/context.rs`
• `crates/zeph-llm/src/provider.rs`