docs: describe conditions and advice for 22 hardware skills by Dong1017 · Pull Request #283 · InferMatrixLab/InferRSI

Dong1017 · 2026-10-31T03:50:47Z

Governing Issue and delivery slice

Refs #91, Round 2 Batch 3.

The requester authorized the parallel bounded continuation. Fill source-supported applicability for 20 hardware owners and add procedure-specific advice across the frozen 22 hardware IDs. Preserve the two existing applicability declarations, including Hopper architecture and mechanism exclusions.

Only applicability/recommendations change in the selected sidecars; source bodies, provenance, maturity and empirical-validation fields are unchanged.

This branch starts from main ffb77f9a168ba1cb22f7ba261f289d24dbb6698f and integrates main 6810870046b4f493d39b6eaede0f1a4004369235, preserving the Sarathi, DistServe and Mooncake source/matrix additions and upstream evidence. Batch 2 remains in #263; the other batches are separate deliveries. Shared projections must be regenerated from combined sources when integrating siblings, preserving all source and matrix additions. A closed applicability key allowlist remains deferred. No new source extraction, model/device execution, paid evaluation or efficacy claim is included.

Checks and provenance

Current head: 270fca4daccae4b4c257f4c2191295219b51256c.
Reachable catalog-source snapshot: b3c091a61e128cb848ca826d2fdc6b8f9d10e6ff, retained before a separate projection commit; the final skill-library inputs are identical to this snapshot. Matrix/code follow-ups are retained in the same PR history. No amend discards the referenced source.
Source-ancestry check, both generator checks and Ruff pass.
All frozen payload IDs, field origins, JSON shapes and preserved applicability values were validated before application. Canonical diff checks confirm only the two authorized fields changed. Current-head Linux Ready CI passes on Python 3.10 and 3.11, including both full suites, both installed-package checks and model-free KV qualification. The Python 3.11 suite reports 3,190 passed, 13 skipped and 284 passing subtests. This applies to 270fca4daccae4b4c257f4c2191295219b51256c; Skill Eval remains planned/unexecuted.
Canonical diff audit preserves all fields outside the accepted slice. Current-head Ready and declaration results are available in this PR's Checks.

These are source and software checks. Independent current-head review is requested; this description is not an approval. Skill Eval execution, efficacy, native-device qualification, merge and whole-tracker closure are not claimed. #91 remains open.

Frozen IDs and field-to-source review pointers

Pointers refer to unchanged source sections in the canonical snapshot above. Existing applicability values are preserved.

Owner	Field origins
ascend-aclgraph-capture-replay	`applicability.scope`: SKILL.md:L8-L12 Trigger and boundary `applicability.prerequisites`: SKILL.md:L22-L26 Required evidence (P) `applicability.input_contract`: SKILL.md:L22-L24 Required evidence (P) `applicability.produced_artifact`: SKILL.md:L42-L46 Verification and failure handling (P) `applicability.refusal_point`: SKILL.md:L26 and L42-L46 Verification and failure handling (P) `recommendations[0]`: SKILL.md:L28-L31 Decision procedure and available actions (P) `recommendations[1]`: SKILL.md:L32-L33 Decision procedure and available actions (P) `recommendations[2]`: SKILL.md:L34-L44 Decision procedure; Verification and failure handling (P)
ascend-device-health	`applicability.scope`: SKILL.md:L22-L28 When to use this skill `applicability.hardware`: SKILL.md:L30-L62 Steps 1 and 2 `applicability.input_contract`: SKILL.md:L30-L91 Steps 1-4 `applicability.produced_artifact`: SKILL.md:L30-L111 Steps 1-5; Card-group change discipline `applicability.failure_modes`: SKILL.md:L62-L111 Steps 2-5; Card-group change discipline `recommendations[0]`: SKILL.md:L30-L76 Steps 1-4 `recommendations[1]`: SKILL.md:L74-L91 Step 4 `recommendations[2]`: SKILL.md:L95-L124 Step 5; Card-group change discipline; Environment variables checklist
ascend-distributed-parallel	`applicability.scope`: SKILL.md:L8-L22 and L91-L107 `applicability.input_contract`: SKILL.md:L24-L52 Native HCCL AllReduce qualification; L91-L123 `applicability.produced_artifact`: SKILL.md:L54-L70 and L253-L286 Attributing differences between parallel strategies `applicability.failure_modes`: SKILL.md:L171-L230 and L278-L286 `recommendations[0]`: SKILL.md:L24-L47 and L101-L107 and L171-L181 `recommendations[1]`: SKILL.md:L34-L52 Native HCCL AllReduce qualification `recommendations[2]`: SKILL.md:L72-L89 and L215-L230 `recommendations[3]`: SKILL.md:L48-L52 and L109-L161 and L253-L276
ascend-graph-mode	`applicability.scope`: SKILL.md:L18-L37 Establish the path before changing an option `applicability.prerequisites`: SKILL.md:L20-L23 and L59-L64 and L140-L147 `applicability.input_contract`: SKILL.md:L20-L35 and L86-L104 `applicability.produced_artifact`: SKILL.md:L130-L161 Discriminate failures; Validation recipe and completion boundary `applicability.failure_modes`: SKILL.md:L86-L128 Trace capture eligibility and fallback; Preserve input and output ownership `recommendations[0]`: SKILL.md:L39-L84 Use the installed configuration surface `recommendations[1]`: SKILL.md:L86-L104 and L130-L137 `recommendations[2]`: SKILL.md:L106-L128 and L140-L154
ascend-model-adaptation	`applicability.scope`: SKILL.md:L14-L16 Choose the versioned owner `applicability.prerequisites`: SKILL.md:L10-L12 and L33-L34 and L99-L106 `applicability.input_contract`: SKILL.md:L20-L65 Debug order; FP8 checkpoints; KV replication with tensor parallelism; L84-L96 `applicability.produced_artifact`: SKILL.md:L33-L34 and L109-L124 Feature-status reporting `applicability.failure_modes`: SKILL.md:L24-L65 and L99-L106 `recommendations[0]`: SKILL.md:L20-L35 Debug order for a new checkpoint `recommendations[1]`: SKILL.md:L10-L12 and L37-L66 `recommendations[2]`: SKILL.md:L84-L106 Multimodal feature validation order; Layer-reduction smoke tests
ascend-operator-profiling	`applicability.scope`: SKILL.md:L8-L26 When to use this skill vs ascend-performance-analysis `applicability.prerequisites`: SKILL.md:L10-L13 and L48-L80 Steps 1 and 2 `applicability.input_contract`: SKILL.md:L71-L122 Steps 2 and 3; L304-L314 perf_summary.py usage `applicability.produced_artifact`: SKILL.md:L98-L191 Steps 3 and 4 `applicability.failure_modes`: SKILL.md:L274-L291 Known limitations and caveats `recommendations[0]`: SKILL.md:L71-L137 Steps 2 and 3 `recommendations[1]`: SKILL.md:L146-L222 Steps 4-6 `recommendations[2]`: SKILL.md:L282-L298 Known limitations and caveats
ascend-operator-tuning	`applicability.scope`: SKILL.md:L29-L33 Relationship to profiling; L91-L100 Staged escalation `applicability.prerequisites`: SKILL.md:L29-L55 Relationship to profiling; Hard gates; Numeric goal `applicability.input_contract`: SKILL.md:L37-L48 and L71-L87 and L182-L194 and L227-L233 `applicability.produced_artifact`: SKILL.md:L182-L196 Iteration discipline; L227-L233 Verification checklist `applicability.refusal_point`: SKILL.md:L29-L67 and L182-L207 `applicability.failure_modes`: SKILL.md:L78-L87 and L200-L220 `recommendations[0]`: SKILL.md:L37-L48 and L182-L194 and L227-L233 `recommendations[1]`: SKILL.md:L71-L100 Metric contract; Staged escalation `recommendations[2]`: SKILL.md:L211-L225 Known limitations (from source)
ascend-optimization-casebook	`applicability.scope`: SKILL.md:L15-L25 How to use this casebook; L29-L179 Bottleneck classes `applicability.prerequisites`: SKILL.md:L15-L23 How to use this casebook `applicability.input_contract`: SKILL.md:L15-L23 and L186-L208 Adding a new case `applicability.produced_artifact`: SKILL.md:L15-L25 and L186-L208 `applicability.refusal_point`: SKILL.md:L207-L208 Adding a new case `recommendations[0]`: SKILL.md:L15-L25 How to use this casebook `recommendations[1]`: SKILL.md:L10-L13 and L58-L60 and L91-L93 and L128-L130
ascend-performance-analysis	`applicability.scope`: SKILL.md:L14-L27 Accepting an automated optimization stage; L44-L46 Five-layer analysis pipeline `applicability.prerequisites`: SKILL.md:L176-L184 Profiling collection prerequisites `applicability.input_contract`: SKILL.md:L16-L23 and L48-L118 and L121-L139 `applicability.produced_artifact`: SKILL.md:L14-L27 and L142-L174 `applicability.failure_modes`: SKILL.md:L66-L118 Five-layer analysis pipeline `recommendations[0]`: SKILL.md:L44-L69 Five-layer analysis pipeline `recommendations[1]`: SKILL.md:L81-L118 Layers 2 and 3 `recommendations[2]`: SKILL.md:L14-L25 and L155-L174
ascend-video-diffusion-optimization	`applicability.scope`: metadata.json#/applicability/scope (existing value preserved) `applicability.hardware`: metadata.json#/applicability/hardware (existing value preserved) `applicability.prerequisites`: metadata.json#/applicability/prerequisites (existing value preserved) `applicability.input_contract`: src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md#1-freeze-the-goal-contract `applicability.produced_artifact`: src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md#7-final-report `applicability.failure_modes`: SKILL.md:L18-L24 Ascend-Specific Layout And Profiler References `recommendations[0]`: SKILL.md:L10-L16 `recommendations[1]`: SKILL.md:L18-L23 Ascend-Specific Layout And Profiler References `recommendations[2]`: SKILL.md:L14 and L24-L27
ascendc-tiling-design	`applicability.scope`: SKILL.md:L95-L213 Reduction, broadcast, elementwise, matmul and conversion routing `applicability.input_contract`: SKILL.md:L30-L91 Universal four-element template; Cross-class rules `applicability.produced_artifact`: SKILL.md:L30-L48 Universal four-element template; L224-L225 Known limitations `applicability.failure_modes`: SKILL.md:L57-L84 Cross-class rules; L191-L202 MatMul routing `recommendations[0]`: SKILL.md:L50-L74 Cross-class rules `recommendations[1]`: SKILL.md:L43-L48 and L62-L70 `recommendations[2]`: SKILL.md:L75-L91 and L179-L230
cann-attribution-overlap	`applicability.scope`: SKILL.md:L43-L77 The chained procedure, Stages 1-3 `applicability.prerequisites`: SKILL.md:L79-L87 Stage 4; L108-L117 Communication-specific rules `applicability.input_contract`: SKILL.md:L45-L77 and L108-L117 `applicability.produced_artifact`: SKILL.md:L65-L106 Stages 3-6 `applicability.failure_modes`: SKILL.md:L50-L77 and L98-L106 and L119-L129 `recommendations[0]`: SKILL.md:L45-L63 Stages 1 and 2 `recommendations[1]`: SKILL.md:L65-L96 Stages 3-5 `recommendations[2]`: SKILL.md:L98-L129 Stage 6; Metric separation rules `recommendations[3]`: SKILL.md:L143-L180 Unresolved conflicts; Later-revision safeguards; OS bridge
cgroup-resource-controls	`applicability.scope`: SKILL.md:L19-L31 SearchSpace mapping; L43-L100 Controller procedures `applicability.prerequisites`: SKILL.md:L102-L116 Hierarchy, delegation, permissions `applicability.input_contract`: SKILL.md:L43-L116 Controller procedures; Hierarchy, delegation, permissions `applicability.produced_artifact`: SKILL.md:L35-L41 Prime rule; L115-L136 Verification contract `applicability.failure_modes`: SKILL.md:L35-L41 and L59-L69 and L89-L100 `recommendations[0]`: SKILL.md:L43-L57 CPU: quota versus contention `recommendations[1]`: SKILL.md:L59-L87 Cpuset; Memory `recommendations[2]`: SKILL.md:L35-L41 and L78-L87 and L129-L136 `recommendations[3]`: SKILL.md:L89-L116 IO; Hierarchy, delegation, permissions
diagnose-attention-bottlenecks	`applicability.scope`: SKILL.md:L10-L12 Trigger and evidence gate `applicability.input_contract`: SKILL.md:L14-L16 Trigger and evidence gate `applicability.produced_artifact`: SKILL.md:L35-L37 Required output and proposed verification `applicability.refusal_point`: SKILL.md:L16 and L41 `recommendations[0]`: SKILL.md:L18-L20 Decision procedure `recommendations[1]`: SKILL.md:L22-L25 Decision procedure `recommendations[2]`: SKILL.md:L25-L31 Decision procedure; Portability gate
host-memory-management	`applicability.scope`: SKILL.md:L8-L31 Intro; Versioned Ascend native descriptor-pool case `applicability.input_contract`: SKILL.md:L33-L86 and L160-L198 `applicability.produced_artifact`: SKILL.md:L21-L23 and L33-L75 and L200-L207 `applicability.failure_modes`: SKILL.md:L48-L75 and L149-L158 `recommendations[0]`: SKILL.md:L56-L75 Asynchronous transfer: three independent obligations `recommendations[1]`: SKILL.md:L33-L54 Pinned host memory: ownership before capacity `recommendations[2]`: SKILL.md:L77-L86 and L143-L158 and L200-L207
host-overhead-optimization	`applicability.scope`: SKILL.md:L8-L33 When to Use; Using Analysis Results `applicability.prerequisites`: SKILL.md:L19-L33 and L87-L95 and L378 `applicability.input_contract`: SKILL.md:L27-L33 and L59-L95 and L127-L146 and L195-L239 `applicability.produced_artifact`: SKILL.md:L232-L239 Phase 6; L361-L370 Final Summary Output `applicability.failure_modes`: SKILL.md:L27-L50 and L107-L111 and L220-L230 and L275 `recommendations[0]`: SKILL.md:L27-L33 and L127-L157 `recommendations[1]`: SKILL.md:L107-L111 and L189-L230 `recommendations[2]`: SKILL.md:L37-L50 and L220-L239 and L266-L275
host-overhead-profiling	`applicability.scope`: SKILL.md:L8-L28 When to Use `applicability.prerequisites`: SKILL.md:L30-L34 Prerequisites; L83-L101 Input validation `applicability.input_contract`: SKILL.md:L12-L15 and L119-L128 Root Cause Phase `applicability.produced_artifact`: SKILL.md:L93-L115 and L168-L175 and L290-L296 `applicability.failure_modes`: SKILL.md:L123-L128 and L281-L286 Pitfalls `recommendations[0]`: SKILL.md:L51-L53 and L75-L79 and L123-L128 and L236-L242 `recommendations[1]`: SKILL.md:L61-L75 and L184-L190 and L290-L296 `recommendations[2]`: SKILL.md:L123-L128 and L281-L286
os-process-placement	`applicability.scope`: SKILL.md:L32-L41 Scope; L45-L108 CPU affinity `applicability.prerequisites`: SKILL.md:L153-L170 Structured environment checks `applicability.input_contract`: SKILL.md:L45-L170 and L172-L185 `applicability.produced_artifact`: SKILL.md:L153-L170 and L204-L211 Verification checklist `applicability.failure_modes`: SKILL.md:L65-L97 and L114-L151 `recommendations[0]`: SKILL.md:L45-L69 CPU affinity `recommendations[1]`: SKILL.md:L75-L108 and L114-L131 and L191-L202 `recommendations[2]`: SKILL.md:L133-L170 Device-busy preflight; Structured environment checks
reason-hopper-kernels	`applicability.scope`: metadata.json#/applicability/scope (existing value preserved) `applicability.architectures`: metadata.json#/applicability/architectures (existing value preserved) `applicability.excluded_mechanisms`: metadata.json#/applicability/excluded_mechanisms (existing value preserved) `applicability.input_contract`: SKILL.md:L20-L26 Establish the actual contract `applicability.produced_artifact`: SKILL.md:L51-L63 Return a reviewable hypothesis `applicability.failure_modes`: SKILL.md:L28-L42 Establish the actual contract; Choose the next discriminating check `recommendations[0]`: SKILL.md:L28-L32 Establish the actual contract `recommendations[1]`: SKILL.md:L34-L42 Choose the next discriminating check `recommendations[2]`: SKILL.md:L58-L63 Return a reviewable hypothesis
storage-io-measurement	`applicability.scope`: SKILL.md:L32-L42 Prime rule; L44-L91 Workload, concurrency and cache procedures `applicability.prerequisites`: SKILL.md:L106-L116 and L139-L159 Proposed safe procedure `applicability.input_contract`: SKILL.md:L44-L54 and L69-L104 and L147-L162 `applicability.produced_artifact`: SKILL.md:L32-L42 and L93-L116 and L147-L162 `applicability.refusal_point`: SKILL.md:L32-L54 and L118-L127 `recommendations[0]`: SKILL.md:L44-L67 Workload matching; Requested versus achieved concurrency `recommendations[1]`: SKILL.md:L69-L91 Cache-state accounting; Startup versus steady-state runs `recommendations[2]`: SKILL.md:L93-L145 Output schema; Device attribution; Saturation-evidence gate; Process attribution `recommendations[3]`: SKILL.md:L147-L162 Proposed safe procedure
torchnpu-device-memory-lifecycle	`applicability.scope`: SKILL.md:L8-L16 Scope and evidence contract; Related capabilities `applicability.input_contract`: SKILL.md:L18-L20 Required evidence `applicability.produced_artifact`: SKILL.md:L34-L40 Countersignals, verification and escalation `applicability.refusal_point`: SKILL.md:L20-L24 and L36 `recommendations[0]`: SKILL.md:L22-L26 Decision procedure and available actions `recommendations[1]`: SKILL.md:L28-L32 Decision procedure and available actions `recommendations[2]`: SKILL.md:L30-L38 Decision procedure; Countersignals, verification and escalation
torchnpu-pinned-host-memory-lifecycle	`applicability.scope`: SKILL.md:L8-L16 Scope and evidence contract; Related capabilities `applicability.input_contract`: SKILL.md:L18-L20 Required evidence `applicability.produced_artifact`: SKILL.md:L34-L40 Countersignals, verification and escalation `applicability.refusal_point`: SKILL.md:L36-L40 Countersignals, verification and escalation `recommendations[0]`: SKILL.md:L22-L24 Decision procedure and available actions `recommendations[1]`: SKILL.md:L26-L28 Decision procedure and available actions `recommendations[2]`: SKILL.md:L30-L32 Decision procedure and available actions

Knowledge authorship declaration

{
  "schema_version": 1,
  "head_sha": "270fca4daccae4b4c257f4c2191295219b51256c",
  "human_only": false,
  "material_ai_authors": [
    {
      "tool": "Codex",
      "model_id": "gpt-6-astra",
      "effort": "xhigh",
      "role": "author"
    }
  ]
}

Preserve source provenance and evidence states while making the declared scope explicit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Keep the canonical source snapshot reachable as a preceding commit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

chatgpt-codex-connector · 2026-10-31T03:50:56Z

Codex Review Summary

This comment shows the latest Codex review activity on this pull request.

Review	Status	Commit	Review trigger
📝 Code Review	⚠️ Failed 2026-10-31T03:51:59.233391Z We couldn’t complete this review. Comment `@codex review` to try again.	`7746aea`	PR opened

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Comment "@codex review" or "@codex security review".

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github-actions · 2026-10-31T03:51:32Z

Skill evaluation

Automatic execution / cumulative PR budget: {"reason":"Trusted configuration or pricing missing, invalid or expired","remaining_usd":"unknown","reserved_or_unresolved_usd":"unknown","spent_or_legacy_usd":"unknown","state":"blocked"}

Advisory: obtain missing evidence

Retained evidence availability: planned / unexecuted. No approval or merge authorization is issued.

Retained evidence is planned / unexecuted.
No supported comparison cases were selected.
Uncovered/unsupported scope needs a case or explicit reviewer disposition.

PLANNED: execution is not authorized by knowing this hash.
Outcomes: {"fix":0,"inconclusive":0,"missing_pair":0,"regression":0,"unchanged_correct":0,"unchanged_incorrect":0}
Earlier revision results are stale for this plan.

Selected comparisons: 0 · Estimated task calls: 0.
Uncovered/unsupported changes: 101. Gaps never count as passes.

Applicable only while these revisions and inputs match the current PR.
Paid execution requires trusted label authorization and cumulative PR reservation. Unknown accounting blocks new paid calls; planning is not execution.
Pipeline evidence only; offline fixed outputs do not establish skill efficacy.
Evidence and logs · Retention: 30 days.
Outcomes are historical; verifiable only before Unix time 1796017749 while the linked artifact is available. Expired evidence is unverified.

Plan bindings, budget, frozen exam and advisory details

Unchanged-correct is valid neutral evidence, not incremental benefit.
Content/source review and authorship admission remain separate.
Trusted regrading checks retained answers, not model/hardware provenance or a hostile executor; this is not an efficacy certification.

Per-case outcomes (discovery excluded; regressions and gaps first):

[]

Showing at most 20 of 0 pairs; the evidence link contains all outcomes, including omitted regressions/gaps.

Plan SHA-256: 14698d6b4d57b60c2254a16fd7cd7a66c6b714d6f6b28441d7b006208d826060
Base: 6810870046b4f493d39b6eaede0f1a4004369235 · Head: 270fca4daccae4b4c257f4c2191295219b51256c
Trusted implementation: 6810870046b4f493d39b6eaede0f1a4004369235

Model/settings: {"effort":"not_applicable","name":"claude-opus-5-5"}
Budget: {"comparisons":0,"estimated_calls":0,"limits_per_comparison":{"campaign_seconds":600,"max_task_calls":2,"repeats":1,"timeout_seconds":180,"token_stop_new_trials":200000},"provider_config_sha256":"b28d80f8194fbe0f5a9f01515efb24b218979fd45f702776560da276f4b30d04","reservation":null}

Skill	Comparison	Cases	Estimated calls

Provider/settings: {"client":{"api_version":"2023-06-01","endpoint":"https://yibuapi.com/v1/messages","kind":"anthropic-messages-full-context-v1","max_output_tokens":4096,"max_read_bytes":32768,"max_request_bytes":262144,"max_requests":1,"max_tool_calls":12,"provider":"yibuapi"},"limits":{"token_stop_new_trials":200000},"model":{"effort":"not_applicable","name":"claude-opus-5-5"},"pricing":{"currency":"USD","expires_at":1793271228,"group":"default","max_input_tokens":1000000,"model":"claude-opus-5-5","rate_evidence":"https://github.com/InferMatrixLab/InferRSI/issues/215#issuecomment-6467531341","rates":{"cache_read":"0.4","cache_write":"10","input":"8","output":"40"},"request_fee":"0","unit":"per_million_tokens"},"spend_limit":{"amount":"200","currency":"USD"}}

Uncovered / unsupported paths (101)

uncovered: "docs/skill-coverage.md"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-video-diffusion-optimization.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-fixed-workload-claim.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-runtime-residency.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-llama-runtime-state.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-recurrent-kv-finalization.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-sd-cpp-residency.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-sglang-diffusion-lifetimes.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/bound-windowed-attention-replay.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/budget-speculative-verification.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/claim-contract.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/comfy-ui.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diffusers-invocation-state.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dwarfstar.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/generation-cache-lifecycle.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/husky.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lithos-metal.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json"
uncovered: "src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/host/cgroup-resource-controls/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/host/host-memory-management/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/host/host-overhead-optimization/metadata.json"
uncovered: "src/inferrsi/data/skill_library/hardware/host/os-process-placement/metadata.json"
Additional paths omitted; see retained evidence.

Dong1017

LGTM for the bounded hardware-sidecar projection at 7746aea5; no blocking source-fidelity or packaging issue found.

All 22 canonical sidecars change only applicability/recommendations. Existing applicability values are preserved, including the Hopper and Ascend video boundaries; source identities, maturity and empirical-validation fields remain unchanged.
The new conditions and advice retain the owning procedures' hardware, ordering/lifetime, measurement and refusal distinctions. They describe source guidance and do not establish native correctness or a performance result.
Current-head Ready and declaration checks pass. Existing author/integrator @Dong1017 should combine canonical sources before regenerating catalog/coverage and checking a new integration head. Skill Eval remains unexecuted; this is neither a merge decision nor acceptance of the overall tracker.

Evidence and scope

Head: 7746aea56298fa2f9df21f92b1a830b8eb8ea4ba; API base / assessed main: ecca7e9136d962747f42860f58e332f45b0aa358 / ecca7e9136d962747f42860f58e332f45b0aa358.
Hosted tested merge: 368ca43a97b8ccf84d43fdec86aeaaef492ef06c, with verified parents current main + this head. Ready run has successful Python 3.10/3.11 full-check and installed-package jobs plus KV task qualification. Latest declaration run succeeds; declaration compliance alone verifies neither author execution settings nor content.
Reviewed scope: All 22 changed hardware sidecars against their owning procedure contracts, the two preserved applicability declarations, canonical allowed-field diff, reachable source pin and affected catalog/coverage projections. Source snapshot a037b99a198c944a4ddbbe1d952bda1f42ab2ffa is public and the library inputs do not change between it and this head; later commits contain projections. This task inspected source and hosted evidence; it did not rerun pytest, generators, models, devices or paid evaluation.
Current Skill Eval plan: zero selected comparisons, 127 uncovered/unsupported changes, execute skipped. Explicit disposition: source/metadata software delivery only, with candidate/not_run and all empirical acceptance gaps retained. Green software checks are not skill-effect evidence.
Sibling combination is untested: #263 a559b12a1dcf1d549e801dd645a949b0f730a75f; #282 8b8ff658d10a143cabac0999900ba27d915bea19; #283 7746aea56298fa2f9df21f92b1a830b8eb8ea4ba; #285 57bc805db9bb56995e2ae988830e1c52a14f85d3; paper additions #277 e3db289c42d6d37374755a05f28b1107da4f73ae, #278 7ef53189343c4bf04fc9e31b4d80f9644482cdfc, #279 cf0b7022761fa83361f986e3b37c2031ad33fd8d. The known findings on #263/#285 are not cleared by this review.
No implementation involvement in this review task. COMMENTED because the posting account is also the PR author account; no formal self-approval is issued.

Retain all upstream source, case, metadata and matrix additions alongside the accepted hardware applicability and recommendations. Keep the source merge reachable for the subsequent generated projection commit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (source integration) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Pin the canonical catalog to the reachable source merge and refresh the coverage view from the same committed input bytes. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (generated projections and validation) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Preserve all 22 hardware applicability and recommendation declarations. Retain upstream canonical sources and matrices before regenerating projections. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Retain the DistServe integration and all 22 hardware guidance declarations. Preserve upstream canonical sources and matrices before final regeneration. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Keep the canonical source snapshot reachable as a preceding commit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Dong1017 added 2 commits October 31, 2026 11:39

docs: describe hardware skill conditions and advice

a037b99

Preserve source provenance and evidence states while making the declared scope explicit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

docs: regenerate skill projections from published source history

7746aea

Keep the canonical source snapshot reachable as a preceding commit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

Dong1017 added the area:knowledge Knowledge line: packs, skill library, knowledge admission label Oct 31, 2026 — with ChatGPT Codex Connector

Dong1017 mentioned this pull request Oct 31, 2026

feat: distinguish resource-layer exclusions and unresolved coverage #282

Open

Dong1017 commented Oct 31, 2026

View reviewed changes

Dong1017 added 5 commits October 31, 2026 12:26

docs: regenerate skill projections from published source history

270fca4

Keep the canonical source snapshot reachable as a preceding commit. Agent-assisted-by: Codex / gpt-6-astra [effort=xhigh] (author) Signed-off-by: Dong1017 <55723162+Dong1017@users.noreply.github.com>

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docs: describe conditions and advice for 22 hardware skills - #283

docs: describe conditions and advice for 22 hardware skills#283
Dong1017 wants to merge 7 commits into
InferMatrixLab:mainfrom
Dong1017:codex/issue91-batch3

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Governing Issue and delivery slice

Checks and provenance

Knowledge authorship declaration

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Skill evaluation

Advisory: obtain missing evidence

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Dong1017 commented Oct 31, 2026 •

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