docs: harden GLM alpha resource and protocol gates

.scratch/distributed-gguf-runtime/issues/06-implement-architecture-defined-boundary-input-output.md

@@ -23,6 +23,8 @@ As a Shard, I need to consume and emit the correct transformer boundary state so
 
 - [ ] Head accepts token IDs and owns token embedding.
 - [ ] Middle/tail bypass token embedding and accept the named boundary bundle.
+- [ ] Amend the decode fast path so `DecodeStep` carries a versioned `TensorBundle`, not one `NamedTensor`; retain a compact one-tensor encoding and fallback compatibility, regenerate Python/C++ schema code, and update protocol goldens.
+- [ ] Define an explicit typed tail result for logits and/or sampled token output, with sampling parameters and chat-template/reasoning mode bound to exact request/recipe identity.
 - [ ] Non-tail emits the unnormalized architecture-defined residual/boundary before final norm/head and before tail-only row pruning.
 - [ ] Tail emits logits or token output through an explicit sampling contract.
 - [ ] Dense-Llama whole-model versus two-range prefill and greedy-decode parity passes the documented tolerance.

.scratch/distributed-gguf-runtime/issues/17-lock-glm-5-2-max-target-and-alpha-contract.md

@@ -27,8 +27,10 @@ As a release owner, I need one exact GLM-5.2 Max target and immutable alpha cont
 - [ ] Pin `zai-org/GLM-5.2` and `unsloth/GLM-5.2-GGUF` by exact observed repository revisions and identify `UD-IQ1_S` as the alpha quantization.
 - [ ] Resolve all six `UD-IQ1_S` filenames, exact byte sizes, LFS SHA-256 values, aggregate decimal GB/GiB, license, and source URLs without downloading the weight payloads.
 - [ ] Snapshot and hash architecture-critical config/tokenizer/chat-template metadata, including main/NextN layer counts, hidden width, experts/top-k, DSA top-k, IndexShare roles, context maximum, and `reasoning_effort=max` behavior.
-- [ ] Generate deterministic minimum-node calculations from exact artifact bytes, configurable per-node reserve, KV dtype/context, scratch reserve, and endpoint/tensor imbalance.
+- [ ] Generate deterministic minimum-node calculations from exact artifact bytes, Q8_0 MLA/indexer KV at 16K context/concurrency 1, endpoint/tensor imbalance, and a per-node reserve of at least `max(20% of physically usable memory, 8 GiB)`.
+- [ ] Classify 224 GiB aggregate runtime-accessible memory as an experimental hard-fit floor, not a conservative envelope; recommend 5×64 GiB or 3×96/128 GiB unless exact measured placement proves an arithmetic-minimum topology.
 - [ ] Count unified system RAM/integrated-GPU memory once and reject additive RAM+VRAM claims for one shared pool.
+- [ ] Lock same-switch wired 2.5 GbE as the alpha minimum and 10 GbE as recommended; model serial seam latency separately from bandwidth.
 - [ ] Lock the identity, semantic correctness, target-run, performance, reliability, and mounted-storage criteria from the roadmap in a machine-readable contract before full target execution.
 - [ ] Refresh and record current upstream llama.cpp GLM-5.2/DSA/IndexShare/MTP support and focused donor candidates; do not adopt a broad donor fork or scheduler.
 - [ ] Add tests that reject changed revisions, missing shards, inconsistent aggregate bytes, duplicate unified-memory accounting, and post-result threshold mutation.

.scratch/distributed-gguf-runtime/issues/18-certify-whole-model-glm-5-2-runtime-semantics.md

@@ -23,7 +23,8 @@ As a runtime maintainer, I need a certified whole-model oracle for the exact low
 
 ## Acceptance criteria
 
-- [ ] Preflight at least 224 GiB usable memory and approximately 250 GB free mounted storage; abort before download if storage would resolve under `/home` or requirements are unmet.
+- [ ] Preflight a 256-GiB-class reference host with at least 224 GiB runtime-accessible memory after OS reservation and approximately 250 GB free mounted storage; abort before download if storage resolves under `/home` or requirements are unmet.
+- [ ] Configure the oracle's alpha lane for 16,384 context, concurrency 1, and Q8_0 MLA/indexer KV; record actual MLA, indexer-cache, scratch, and peak resident allocations separately.
 - [ ] Download/resume and verify all six DGR-017 `UD-IQ1_S` files against exact sizes and LFS SHA-256 values.
 - [ ] Load the target with the unmodified DGR-004 pin first and retain full logs, tensor warnings, peak memory, context/KV allocation, TTFT, and decode timing.
 - [ ] Prove from graph/runtime evidence whether 256-expert MoE/top-8/shared expert, DSA lightning indexer/sparse attention, IndexShare Full/Shared reuse, and `reasoning_effort=max` are active.
@@ -47,7 +48,7 @@ As a runtime maintainer, I need a certified whole-model oracle for the exact low
 
 ## Finish contract
 
-- If 224+ GiB usable reference hardware is unavailable, write `evidence/DGR-018/BLOCKED.md` with exact preflight output; do not substitute a smaller model.
+- If a 256-GiB-class host with at least 224 GiB runtime-accessible memory is unavailable, write `evidence/DGR-018/BLOCKED.md` with exact preflight output; do not substitute a smaller model.
 - Preserve real failures and blockers; never fabricate output.
 - Emit `<promise>COMPLETE</promise>` only after the signed oracle evidence exists.
 

.scratch/distributed-gguf-runtime/issues/20-pass-real-distributed-glm-5-2-max-alpha.md

@@ -24,12 +24,14 @@ As an alpha user, I need the exact lowest-quant GLM-5.2 model to run in Max reas
 ## Acceptance criteria
 
 - [ ] Use the exact DGR-017 `UD-IQ1_S` artifact and certified DGR-018/DGR-019 runtime recipe with all source and patch hashes verified.
-- [ ] Use at least two physical consumer machines with at least 224 GiB aggregate usable admitted memory; no participating node may individually admit the complete recipe and unified memory is counted once.
+- [ ] Use at least two physical consumer machines; each reserves at least `max(20% of physically usable memory, 8 GiB)` outside weight-plus-Q8-KV placement, no node can place the complete recipe, unified memory is counted once, and measured peak use stays within physical memory without swap/overcommit.
+- [ ] Treat 5×64 GiB or 3×96/128 GiB as the recommended topology; arithmetic-minimum 4×64 or 2×128 qualifies only with exact contiguous placement and measured reserve evidence.
+- [ ] Use a same-switch wired network with at least 2.5 GbE; record 10 GbE as recommended and measure hop RTT/serialization/queue latency.
 - [ ] Tracker selects disjoint contiguous Shards whose exact required tensor inventory has complete union and no unintended overlap.
 - [ ] Every stage reports real CPU/GPU compute, owned tensor bytes/layers, local KV, backend, queue, and seam telemetry; synthetic, passthrough, or zero-layer workers fail acceptance.
 - [ ] Runtime evidence proves native GLM MoE/shared expert, DSA lightning indexer/sparse attention, and IndexShare Full/Shared paths are active; dense fallback fails acceptance.
 - [ ] OpenAI-compatible API applies and records `reasoning_effort=max`, stable model ID, finish reason, and token usage.
-- [ ] Configure 16,384 context; complete the fixed 4,096-token prefill lane and generate at least 512 output tokens or valid natural EOS after at least 128 tokens.
+- [ ] Configure 16,384 context, concurrency 1, and Q8_0 MLA/indexer KV; complete the fixed 4,096-token prefill lane and generate at least 512 output tokens or valid natural EOS after at least 128 tokens.
 - [ ] Production seam meets at least 0.90 greedy token agreement and 0.999 mean compared-state/logit cosine similarity against DGR-018 on the fixed corpus, with no non-finite or malformed tensors.
 - [ ] Fixed coding, structured tool-call/JSON, and multi-step reasoning sentinels produce parseable relevant outputs retained for human review.
 - [ ] After warm-up, fixed Max lane median decode is at least 0.5 token/s, 4,096-token-prompt TTFT is at most 10 minutes, and no unexplained stall exceeds 60 seconds without progress telemetry.