Recommends and auto-discovers Qwen3-Coder-30B-A3B-Instruct as the
default model for `apr code` when present. Aligned with the
research write-up at paiml/claude-code-parity-apr / 2026-04-28.

What ships:

  configs/aliases.yaml
    + new short name `qwen3-coder` →
      hf://unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
    Now `apr pull qwen3-coder` works.

  crates/aprender-registry/src/aliases.rs
    + matching entry in the in-memory AliasRegistry
      (kept in sync with configs/aliases.yaml).

  crates/aprender-orchestrate/src/agent/manifest.rs
    + `~/.cache/pacha/models/` added to model_search_dirs so
      `apr pull`-cached files (content-hashed names) are visible
      to discovery; pair with a friendly symlink in
      `~/.apr/models/` for the preferred-name filter to recognize.
    + new module-level helper `is_preferred_default_model(path)`:
      case-insensitive substring match against a short list of
      recommended-default model names. Order:
        1. qwen3-coder-30b-a3b
        2. qwen3-coder-next
        3. qwen2.5-coder-32b
        4. qwen2.5-coder-14b
    + discover_model + sort_candidates updated to insert
      preferred-name as a sort key BETWEEN validity (still wins
      overall) and newest-mtime. So when a small recently-pulled
      model exists alongside the recommended default, the
      recommended default is selected — fixing the failure mode
      where Qwen3-1.7B (PMAT-190 thinking-loop bug, emits
      gibberish) was being auto-picked over a known-good 30B model.

Tests (5 new in manifest_tests_discovery.rs, 49 → 54 in agent::manifest):
  - preferred_default_recognises_qwen3_coder_30b_a3b
    (any-case, any-quant matching)
  - preferred_default_rejects_small_fallbacks
    (1.7B / 1.5B / 1.1B / 7B all rejected — the 7B Qwen2.5-Coder is
    still useful but we don't anchor it as the recommended-default
    family for 24 GB GPUs)
  - sort_candidates_promotes_preferred_over_newer
    (preferred-name beats newer-but-smaller mtime)
  - sort_candidates_newer_preferred_beats_older_preferred
    (within preferred-names, mtime still tiebreaks)
  - sort_candidates_validity_outranks_preference
    (Jidoka — invalid preferred loses to valid non-preferred)

Live verification (this PR):

  $ apr pull qwen3-coder
    ✓ Downloaded successfully
      Path: /home/noah/.cache/pacha/models/2b88b180a790988f.gguf
      Size: 17.3 GB

  $ ln -s /home/noah/.cache/pacha/models/2b88b180a790988f.gguf \
         /home/noah/.apr/models/Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf

  $ apr code -p "ping" --max-turns 1
    Model: Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf (auto-discovered)
    ↑ default-model preference picked correctly.

Known gap (NOT addressed by this PR):

  After auto-discovery picks the model, both apr-serve subprocess
  and embedded inference fail with:

    Error: driver error: inference failed:
           Invalid shape: Tensor 'blk.0.ffn_up.weight' not found

  Qwen3-Coder-30B-A3B is a Mixture-of-Experts model that uses
  per-expert tensor names (`ffn_up_exps`, `ffn_gate_exps`, etc.),
  not the dense `ffn_up.weight` the current realizar GGUF loader
  expects. qwen3moe architecture support is upstream realizar
  work — separate from this PR. The discovery / alias / preferred-
  name selection mechanism is fully ready for when that lands.

  In the interim users hitting the inference error should fall
  back to a dense model — either Qwen2.5-Coder-32B-Instruct
  (also recognized by is_preferred_default_model) or Qwen2.5-Coder-7B.

Refs:
  - Research write-up: paiml/claude-code-parity-apr / chat 2026-04-28
  - Hugging Face: unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
  - aprender CLAUDE.md § Claude Messages-API proxy spec — same model
    is already declared as the default for `apr serve anthropic`

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

…r capture (unblocks SHIP-007 layer-0 bisection)

Triggering observation 2026-04-28: SHIP-007's hypothesis space has been
narrowed by 5 falsified hypotheses (§28, §28.4(a), §31, §32, #1101).
The remaining bug surface is per-element divergence at some specific
stage of layer-0 forward. Aggregate stats — already emitted by
`apr trace --payload` — are insufficient since they can hide per-element
drift behind similar std values.

This contract defines the missing infrastructure: `--save-tensor <stage>`
flag that captures raw F32 tensor values at chosen forward-pass stages,
written as APRT-magic-prefixed binaries that `apr diff --values` can
load directly.

## Stages enumerated (19 total)

embedding, attn_norm, qkv_matmul, qkv_bias, q_post_rope, k_post_rope,
attention, attn_out, post_attn_residual, ffn_norm, ffn_gate, ffn_up,
ffn_silu, ffn_swigl, ffn_out, post_ffn_residual, layer_output,
final_norm, lm_head

## Falsification tests (8)

- 001: --save-tensor flag recognized
- 002: determinism (byte-identical across runs)
- 003: ffn_gate stage produces expected APR-vs-GGUF diff (corroborates #1099)
- 004: APRT header format self-describing
- 005: multi-stage comma-list works
- 006: NaN preservation
- 007: --layer subset compatible
- 008: pv validates

`pv validate` exits 0 (verified).

## Implementation cost

400-600 LOC + 8 tests, multi-day Rust task.

## Linkage to shipping MODEL-1

Once shipped, the SHIP-007 layer-0 bisection completes in one debug
session: run save-tensor in both APR and GGUF formats, apr diff at each
stage, pinpoint the first divergent stage as the actual bug surface.

SHIP-002/005/006/007/008 (5 PARTIALs) all depend on the SHIP-007 fix.
With this tooling, the fix is unblocked.
paiml/qwen2.5-coder-7b-apache-q4k-v1 ships cleanly through both APR
and GGUF backends → MODEL-1 completes.

Status: PROPOSED. Implementation deferred to multi-day Rust task.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>