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Inference known good config

Skill cfregly/gpu-perf-tune/plugins/profile-and-optimize/skills/inference-known-good-config

Capture + enforce per-model KNOWN-GOOD serving configs: the REQUIRED serve flags (boot-blockers / crash-at-high-c / deploy-correctness workarounds) plus the champion + the bug each flag avoids, in one queryable registry (perf-tune-report/configs/known-good-configs.yaml) so a hard-won workaround (e.g. Qwen3-Next's gdn_prefill_backend=triton on vLLM 0.22) is NEVER re-discovered the hard way. These are NOT well-known upstream defaults -- several are field-discovered workarounds where the upstream `auto` path is actively broken on the target hardware. `record` after a champion is found, `check` (fail-closed) before any deploy/ship. Keep the registry private -- never post an entry publicly. Triggers on "known-good config", "required flags for <model>", "did we capture the flag combo", "register the config", "check the deploy config", "config drift", "what flags does <model> need", or any combination of "known-good / required / champion config" with "record / check / register / capture / drift / flags / serve".From its SKILL.md

Install
npx -y skills add cfregly/gpu-perf-tune --skill inference-known-good-config

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inference-known-good-config

Purpose

Make per-model serving-config knowledge durable, queryable, and enforced. The serve flags a model REQUIRES to run correctly (not its full champion config -- the boot-blockers / crash-avoiders / deploy-correctness workarounds) are otherwise scattered across bring-up docs, my-values-*.yaml, arms.tsv, and cross-engine sweep docs, so the next operator re-discovers them the hard way. This skill captures them in ONE registry and makes a deploy that DROPS a required flag a fail-closed error.

The motivating failure: Qwen3-Next on vLLM 0.22 auto-selects the FlashInfer Blackwell GDN prefill kernel, which WEDGES at c>=~8 on the interleaved-GQA layout (decode->0, EngineCore hang). The fix is one flag -- --additional-config '{"gdn_prefill_backend":"triton"}' -- that is not a well-known combination. It is a field-discovered workaround. Without a registry it would be re-discovered each time the model is redeployed.

Backed by two native MCP verbs:

  • known_good_config_record -- append a NEW model entry (comment-preserving).
  • known_good_config_check -- diff a deploy's serve args vs the registry, fail-closed (nonzero) on a missing boot-blocker / crash-high-c / deploy-correctness flag.

When to use

  • After finding a champion (end of inference-tune-sweep / inference-model-optimize): record the model's required flags + champion pointer + evidence. This is part of the grind-closure gate -- a champion is not "closed" until its known-good config is registered (see "Next lever (the grind ratchet)" below).
  • Before any deploy/ship: check the deploy's serve args (or its -f manifest) vs the registry. A missing required flag is fail-closed. To run the check automatically on a vllm serve / kubectl apply, wire known_good_config_check as a pre-exec guard hook using the runtime-agnostic hook contract in hooks/README.md (this repo does not ship that guard pre-wired. The two shipped gates there show the pattern).
  • When an operator asks "what flags does <model> need" / "did we capture that workaround".

Do NOT use this for the FULL champion config -- that stays in my-values-<slug>.yaml / the deploy YAML (the registry points at it via champion.config_ref, never duplicates it).

Example prompts

  • "Record the Qwen3-Next known-good config: it needs gdn_prefill_backend=triton on 0.22."
  • "Check this deploy file against the known-good registry before I apply it."
  • "What required flags does MiniMax-M2.7 need at high concurrency?"
  • "Did we capture the gdn_prefill_backend=triton workaround anywhere durable?"

Prerequisites

  1. Registry -- perf-tune-report/configs/known-good-configs.yaml (schema known_good_config_v1). Resolved via --registry, then $KNOWN_GOOD_CONFIG_REGISTRY, then a walk-up from cwd.
  2. Model id -- the HF id / served-model-name (the registry key).
  3. For check: the deploy's serve args (--serve-args "<joined args>") OR a --deploy-file.

Interaction style

Autonomous for check (it is a gate. Run it). One pause for record: confirm the required-flag tuple(s) + evidence path before the append.

Workflow

record (after a champion / a newly-discovered required flag)

mcp__profile_and_optimize__known_good_config_record with:
  args: ["--model", "<hf-id>",
         "--slug", "<bundle-slug>", "--arch", "<arch note>", "--hardware", "<hw>",
         "--engine", "vllm",
         "--required-flag", "<flag>|<match-regex>|<severity>|<why>|<affected>|<evidence-path>",
         "--champion-config-ref", "<my-values / deploy yaml path>",
         "--champion-verdict", "DRAFT <n> | VERDICT <n>",
         "--champion-campaign", "<campaign-id>",
         "--grind-frontier", "value-findings.yaml -> <model> next_lever",
         "--json"]
  • severity is one of boot-blocker | crash-high-c | deploy-correctness | perf. The first three are fail-closed in check, perf is a warning.
  • record is append-only + comment-preserving. An EXISTING model fails with guidance to edit the YAML by hand (a programmatic rewrite would strip the LOUD banner + per-entry prose). Updating a champion verdict (DRAFT->VERDICT) is a hand-edit.

check (before deploy/ship. Fail-closed)

mcp__profile_and_optimize__known_good_config_check with:
  args: ["--model", "<hf-id>",
         "--deploy-file", "<deploy.yaml>",      # OR --serve-args "<joined args>"
         "--json"]
  • Returns verdict: pass|fail + missing_required: [...]. A missing boot-blocker/crash-high-c/deploy-correctness flag -> fail + nonzero exit (the gate blocks).
  • --require-registered makes an unregistered model a failure (used by the grind-closure gate so a champion must be captured here before it is "closed").

Registry layout

perf-tune-report/configs/known-good-configs.yaml   # schema: known_good_config_v1
  models:
    - model: <HF id>            # the key
      slug, arch, hardware, engine
      required_flags:           # boot-blocker / crash-high-c / deploy-correctness / perf
        - {flag, match, severity, why, affected, evidence}
      champion: {config_ref, verdict, campaign}   # pointer, NOT the full config
      fallback: <a known-working alternative>
      grind_frontier: <cross-ref into value-findings.yaml next_lever>

Safety

  • Keep the registry private. Never post a registry entry (flags, model names, a not-yet-reported upstream bug) to a public repo / upstream / chat without explicit per-turn operator approval.
  • Append-only + comment-preserving for record. The LOUD banner + per-entry why prose are load-bearing and must survive.
  • Fail-closed check is the point -- do not work around a fail by stripping the flag from the registry. Either add the flag to the deploy, or (if it is a genuinely superseded requirement) hand-edit the registry with evidence.

Verdict rigor (DRAFT vs VERDICT)

Per docs/METHODOLOGY.md "Verdict rigor: DRAFT vs VERDICT", a champion.verdict is DRAFT until variance-controlled (same-node, >=3 trials, mean+/-std, metric-isolated, fair baseline). Record the honest tier in the entry. Promote DRAFT->VERDICT by a hand-edit once the controlled A/B lands.

Next lever (the grind ratchet)

Per docs/METHODOLOGY.md "Always be grinding": every record MUST set grind_frontier (the cross-ref into configs/value-findings.yaml next_lever). A known-good config is the CONFIG half of closure, value-findings.yaml is the GRIND half. The grind-closure gate checks BOTH before a champion is "closed": known_good_config_check --require-registered for the CONFIG half, and a recorded next_lever in value-findings.yaml for the GRIND half.

Source-of-truth references

  • configs/known-good-configs.yaml -- the registry.
  • configs/value-findings.yaml -- the paired GRIND FRONTIER (next_lever).
  • docs/METHODOLOGY.md -- verdict rigor + the grind ratchet (the CONFIG-half rule).
  • server/tools/known_good_config/known_good_config_cli.py -- the verb implementation.

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