chopratejas--headroom/REALIGNMENT/00-overview.md

00 — Overview & Wrong Mental Model

Executive summary

Headroom is built on the wrong mental model: "compression means choosing what to drop from conversation history." The flagship IntelligentContextManager (ICM) tokenizes the entire messages array, scores each message for importance, and removes old messages until the budget is hit. It has been wired into the Rust proxy on /v1/messages with frozen_message_count: 0 hardcoded — so every compression event drops messages from index 0, busting the Anthropic prompt cache for every customer that triggers it.

The correct mental model — confirmed by an authoritative engineering guide and ten parallel deep-audit subagents — is the opposite: "passthrough is sacred; compress only the live zone, type-aware, hash-keyed, position-preserving, with side-channel metadata." The cache hot zone (system prompt, tools, old turns, reasoning/thinking/redacted/compaction items) is never touched.

The audit found:

• 5 top-tier cache-killer bugs all stemming from the wrong model
• ~10 K LOC of architectural over-build (ICM + scoring + relevance + rolling-window + progressive-summarizer + tool-crusher + cache-aligner rewrite path + most of crates/headroom-core/src/{context,scoring,relevance}/)
• Wire-format gaps in the streaming SSE parser (missing thinking_delta, signature_delta, citations_delta; UTF-8-split corruption; single-\n SSE split bugs in fallback paths)
• Bedrock/Vertex parity is fake — a lossy LiteLLM Anthropic-to-OpenAI conversion drops thinking, redacted_thinking, document, search_result, image, server_tool_use, mcp_tool_use blocks
• No tool-definition normalization anywhere
• No auth-mode awareness — PAYG, OAuth, and subscription CLIs all get the same policy and the same fingerprint-leaking re-serialization
• X-Headroom-* request headers leak upstream, plus anthropic-beta mutation and OpenAI-Beta auto-injection — fingerprint-class subscription-revocation risks
• CCR markers are computed but never injected into the outgoing request body in the Rust path; the ccr_retrieve tool flips on/off per request — busts the tools array on every state change

What changes

The realignment is structured in 9 phases, 40 PRs, ~13 weeks sequential or ~8 weeks with parallel work:

• Phase A — Lockdown (1 week): stop the cache bleeding immediately. Make /v1/messages compression a passthrough; stop mutating the system prompt; switch Python forwarders from httpx ... json=body (re-serializes) to httpx ... content=raw_bytes; honor customer-set cache_control markers in Rust; strip x-headroom-* from upstream-bound headers; pin anthropic-beta order and make it session-sticky; add a SHA-256 byte-faithful round-trip test.
• Phase B — Live-zone engine (2 weeks): delete ICM, scoring, relevance, rolling-window, progressive-summarizer, tool-crusher (~10 K LOC). Build a live-zone-only block dispatcher in Rust that runs SmartCrusher / LogCompressor / DiffCompressor / SearchCompressor / KompressCompressor on the latest user message content + latest tool_result + latest function_call_output + latest local_shell_call_output. Token-validate every compression with fallback. CCR hardens: persistent backend + always-on ccr_retrieve tool registration.
• Phase C — Rust proxy paths (3 weeks): byte-level SSE parser with full state machine; /v1/chat/completions, /v1/responses (HTTP and streaming) handlers; per-item-type passthrough preservation (V4A patches, local_shell_call.action.command argv, Codex phase field, MCP items, compaction).
• Phase D — Bedrock/Vertex native (2 weeks): delete the LiteLLM lossy converter; build native /model/.../invoke (AWS) and /v1beta1/projects/.../publishers/anthropic/.../streamRawPredict (GCP) routes with SigV4 + ADC signing. Cache fidelity restored on Bedrock/Vertex traffic.
• Phase E — Phase 3 cache stabilization (1 week): sort tool array deterministically; sort JSON Schema keys recursively; auto-place up to 4 cache_control breakpoints (Anthropic); auto-inject prompt_cache_key (OpenAI); volatile-content detector with customer warning (no rewrite); cache-bust drift telemetry.
• Phase F — Auth-mode policy (1 week): classify_auth_mode(headers) helper returning payg | oauth | subscription; per-mode compression policy gates; TOIN aggregation key extended to (auth_mode, model_family, structure_hash); conditional X-Forwarded-* headers in Rust.
• Phase G — RTK + observability (1 week): extend wrap CLIs (cline, continue, goose, openhands); wire the dead tokens_saved_rtk field; per-invocation RTK Prometheus metrics.
• Phase H — Python retirement (2 weeks): delete headroom/proxy/server.py, all handlers, responses_converter.py, memory_handler.py, memory_tool_adapter.py, batch.py, semantic_cache.py, all of headroom/transforms/* Python (per Phase B); keep CLI wrappers, RTK installer, evals, learn, memory writers, tokenizers, TOIN.
• Phase I — Test infra (continuous, parallel): SHA-256 round-trip tests; SSE corner-case fixtures (UTF-8 split, ping, all delta types, [DONE], mid-stream error); property tests (no-panic SSE parser, tokens-non-increasing compression); cache-hit-rate continuous metric; promote ccr / log_compressor / cache_aligner parity comparators from Skipped stubs to real; make make test-parity a per-PR gate.

Top 5 wrong assumptions

1. "Compression means choosing what to drop from history." Implemented as ICM + DropByScoreStrategy + MessageScorer + relevance + scoring + rolling-window + progressive-summarizer. Fix: retire entirely; compress live-zone content only.
2. "TOIN can influence per-request compression decisions." headroom/telemetry/toin.py:853-927 mutates pattern state during a call and returns hints that bias the same-input-bytes decision. Fix: strict observation-only; recommendations published between deploys.
3. "CCR can mutate the cache hot zone (tools array, system prompt) on demand." headroom/ccr/tool_injection.py:302-328 only adds ccr_retrieve when content was compressed — tools list flips between requests. cache_aligner.py:160-262 and headroom/proxy/server.py:1051 rewrite the system prompt. Fix: register ccr_retrieve on every request; route memory injection to the live zone tail; delete the cache_aligner rewrite path.
4. "Summarizing past turns is a strategy." intelligent_context.py:316-353 SUMMARIZE replaces messages with a single summary at the same position — head modification. Fix: delete; offer compaction only as an explicit customer-initiated action.
5. "ToolCrusher operates on every tool message in history without a frozen check." headroom/transforms/tool_crusher.py:106 iterates all tool messages. Fix: delete; ContentRouter covers the use case correctly.

What's preserved

Per your direction:

• TOIN (Tool Output Intelligence Network) — observation-only refactor; per-tenant key
• CCR (Compress-Cache-Retrieve) — persistent backend + always-on tool
• Kompress-base — plain-text §8.6 compressor; stays in Python now, Rust port via ort crate later
• ContentRouter — Python ~2150 LOC, the architecturally correct piece (NOTE: earlier project memory said 53 K lines — that was wrong by 25×; the file is fine)
• All per-type compressors: SmartCrusher (Rust 25 files), CodeCompressor, LogCompressor, SearchCompressor, DiffCompressor

What's deleted

~25 K LOC across two languages. See 01-bug-list.md §6 for the full retirement list with file:line evidence.