Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@docs/parallelisms.md`:
- Around line 508-512: Update the broken cross-reference in
docs/parallelisms.md: replace the non-existent
../knowledge/techniques/parallelism_strategies.yaml link with the relocated card
path under skills/perf-techniques (e.g.,
../skills/perf-techniques/parallelism-strategies/card.yaml) so the "Knowledge
card" link in the "Related Artifacts" section points to the correct card.yaml;
edit the link text that currently references parallelism_strategies.yaml and
ensure it matches the directory name used by the existing skill file
(parallelism-strategies) and the card.yaml filename.

In `@docs/training/communication-overlap.md`:
- Around line 12-13: Update the stale skill file references that point to
pre-split markdown files by changing them to the new per-technique SKILL.md
layout: replace `skills/perf-techniques/tp-dp-comm-overlap.md` with
`skills/perf-techniques/tp-dp-comm-overlap/SKILL.md` and replace
`skills/perf-techniques/expert-parallel-overlap.md` with
`skills/perf-techniques/expert-parallel-overlap/SKILL.md`; also apply the same
path updates to the other occurrences noted (101-102) so all references point to
the new SKILL.md locations.

In `@docs/training/cuda-graphs.md`:
- Around line 45-56: The docs use two different RNG-tracker
names—cfg.rng.te_rng_tracker in the example and use_te_rng_tracker in the
constraints—so pick one and make them consistent; update the constraint line to
refer to the same symbol used in the example (cfg.rng.te_rng_tracker) or
conversely change the example to use use_te_rng_tracker, and ensure the
constraint referencing cuda_graph_impl still reads "cfg.rng.te_rng_tracker must
be True when cfg.model.cuda_graph_impl != 'none'".
- Line 1: The new document docs/training/cuda-graphs.md is orphaned; update the
relevant toctree by adding a reference to "training/cuda-graphs.md" in the docs
index—specifically edit docs/index.md (or the appropriate docs/training index)
and insert the relative path or title entry into the toctree/list so the page is
included in the site navigation; ensure the entry matches the existing toctree
style and run a local docs build to verify the warning is resolved.

In `@docs/training/hybrid-context-parallel.md`:
- Around line 7-8: Update the opening pointer string that currently references
"skills/perf-techniques/hybrid-context-parallel.md" to use the new layout path
"skills/perf-techniques/hybrid-context-parallel/SKILL.md" so the link matches
the rest of the file; search for the literal reference
"skills/perf-techniques/hybrid-context-parallel.md" and replace it with
"skills/perf-techniques/hybrid-context-parallel/SKILL.md".
- Around line 1-8: The new doc "Hybrid / Hierarchical Context Parallel"
(hybrid-context-parallel.md) is not listed in any Sphinx toctree and will be
orphaned; update the relevant toctree (e.g., add an entry in docs/index.md or
the training toctree that aggregates docs/training/*.md) to include
"training/hybrid-context-parallel.md" so the page is reachable in the built docs
and the toc.not_included warning is resolved.

In `@docs/training/megatron-fsdp.md`:
- Line 10: The docs reference the old path
"skills/perf-techniques/megatron-fsdp.md" which is stale; update all internal
links in docs/training/megatron-fsdp.md that point to
"skills/perf-techniques/megatron-fsdp.md" (including the occurrences around the
top and near line 100) to the new path
"skills/perf-techniques/megatron-fsdp/SKILL.md" so internal navigation works;
ensure you replace every exact match of the old filename string with the new
"SKILL.md" path.

In `@docs/training/packed-sequences.md`:
- Around line 8-10: The docs reference
'skills/perf-techniques/sequence-packing.md' which no longer exists; update
every occurrence (including the one at lines ~83-89) to point to the relocated
guide 'skills/perf-techniques/sequence-packing/SKILL.md' so links resolve
correctly; search the file for the string "sequence-packing.md" and replace it
with "sequence-packing/SKILL.md" in the content and any link markup (the
affected file is docs/training/packed-sequences.md).

In `@docs/training/resiliency.md`:
- Around line 15-24: The table entry for "Local checkpointing" is missing its
corresponding documentation sections; add a matching "Local checkpointing"
feature block with "When to Use It" and "Stable Constraints" (and any other
sections used for other features like motivation/usage) following the exact
structure and tone used for entries such as "Async checkpoint save" and
"Preemption", or if this feature should not be documented yet, remove the "Local
checkpointing" row from the table to keep the table consistent; locate
references to "Local checkpointing" in the doc and implement the new sections
with clear guidance on motivation, technical approach, architecture, usage
examples, and implementation details to satisfy the project documentation
requirements.

In `@skills/perf-techniques/expert-parallel-overlap/card.yaml`:
- Around line 27-33: Update the card's known_constraints to mirror the runtime
checks in src/megatron/bridge/training/comm_overlap.py: add a constraint that
moe_shared_expert_overlap must be disabled/false (referencing the
moe_shared_expert_overlap check), require torch version >= 2.6.0 (referencing
the torch version check), and enumerate the recompute-related constraints
enforced in the file (recompute_granularity, recompute_method,
recompute_num_layers) plus the mtp_num_layers constraint so configurations
failing those checks are rejected by the card; ensure each constraint references
the exact setting names used in the code (moe_shared_expert_overlap,
recompute_granularity, recompute_method, recompute_num_layers, mtp_num_layers,
torch version) and phrase them consistently with the existing items.

In `@skills/perf-techniques/expert-parallel-overlap/SKILL.md`:
- Around line 106-110: Update the "Success criteria" in SKILL.md to remove the
hard-coded "41 passed" count and instead require that the targeted test files
pass with zero failures; specifically replace the "41 passed" bullet with a
statement that tests under test_comm_overlap.py (MoE overlap and delayed-wgrad
validation) and test_deepep.py (DeepEP/HybridEP helper activation and GPU
gating) must pass with no failures, so the criteria track those files rather
than a total pytest number.
- Around line 41-49: Add the missing hard requirement that
moe_shared_expert_overlap = False to the "Required constraints" list because the
code asserts this when overlap_moe_expert_parallel_comm is enabled; update
SKILL.md's constraints block to include the exact constraint
"moe_shared_expert_overlap = False" alongside the other items and mention it
applies whenever overlap_moe_expert_parallel_comm is true so readers know it's
not optional.

In `@skills/perf-techniques/hybrid-context-parallel/card.yaml`:
- Around line 51-60: The evidence list in card.yaml references five files that
don't exist; either add the missing files (create
scripts/verify_hybrid_context_parallel.py and the four Megatron-LM stubs under
3rdparty/Megatron-LM/megatron/core and megatron/training) or remove those
entries from the evidence array to keep the card accurate; locate the evidence
key in skills/perf-techniques/hybrid-context-parallel/card.yaml and update it so
only existing files (src/megatron/bridge/training/initialize.py, config.py,
model_load_save.py, and docs/performance-guide.md) remain or add the missing
files with the expected verification script and Megatron modules.

In `@skills/perf-techniques/hybrid-context-parallel/SKILL.md`:
- Around line 94-103: The documentation references a missing verification script
scripts/verify_hybrid_context_parallel.py in SKILL.md which causes "No such
file" errors; either add the missing script or remove/update the verification
commands. Locate the SKILL.md section that runs the verification (the
CUDA_VISIBLE_DEVICES... uv run python -m torch.distributed.run commands) and (a)
if the verification logic exists elsewhere, point the commands to the correct
script/module name and update the examples, or (b) if the verification is
intended to be provided, implement scripts/verify_hybrid_context_parallel.py
matching the CLI flags (--mode mpu/decentralized) and expected behavior, or (c)
remove the verification subsection entirely; update the README references and
any mentions of verify_hybrid_context_parallel.py accordingly.

In `@skills/perf-techniques/megatron-fsdp/card.yaml`:
- Around line 3-6: The torch_fsdp2_runtime status in the card.yaml is
inconsistent with the documented failure in known_limitations; update the
torch_fsdp2_runtime field (in skills/perf-techniques/megatron-fsdp/card.yaml)
from "unclear" to an explicit status reflecting the runtime failure (e.g.,
"failed" or "runtime_failure") and ensure the value aligns with the
known_limitations note about the Torch FSDP2 TypeError from pg_collection so
readers see the runtime failure state consistently.

In `@skills/perf-techniques/megatron-fsdp/SKILL.md`:
- Around line 27-35: The example config block for Megatron FSDP is missing the
cfg.ddp.average_in_collective = False override and thus diverges from the
recommended minimal override and perf-harness overrides; update the snippet that
sets cfg.dist.use_megatron_fsdp, cfg.ddp.use_megatron_fsdp,
cfg.ddp.data_parallel_sharding_strategy, cfg.checkpoint.ckpt_format,
cfg.checkpoint.save, and cfg.checkpoint.load to also set
cfg.ddp.average_in_collective = False so the copy-paste example matches the
recommended override set.

In `@skills/perf-techniques/parallelism-strategies/SKILL.md`:
- Around line 207-208: The cross-reference path in the paragraph mentioning
`skills/perf-techniques/tp-dp-comm-overlap.md` is incorrect; update that
reference to the correct target
`skills/perf-techniques/tp-dp-comm-overlap/SKILL.md` so the link points to the
existing SKILL.md file (edit the occurrence of
`skills/perf-techniques/tp-dp-comm-overlap.md` in the current `SKILL.md` file
and replace it with `skills/perf-techniques/tp-dp-comm-overlap/SKILL.md`).

In `@skills/perf-techniques/sequence-packing/SKILL.md`:
- Around line 39-44: The doc block must mention that enabling pad_cu_seqlens
requires packed-sequence metadata to be present; update the text to explicitly
state that when cfg.dataset.packed_sequence_specs.pad_cu_seqlens = True you must
supply packed-sequence metadata for your dataset (or disable pad_cu_seqlens),
because the dataset code (see src.megatron.bridge.data.datasets.sft assertion in
the packed-sequence handling) will assert that metadata exists; reference
pad_cu_seqlens, cfg.dataset.dataset_kwargs["pad_to_max_length"], and the
assertion in the sft dataset so users with custom packed datasets know to
generate/provide the required packed metadata.

In `@skills/perf-techniques/tp-dp-comm-overlap/card.yaml`:
- Around line 31-36: Add a new known_constraints entry stating that TP overlap
requires Transformer Engine to be present; specifically mention that TP overlap
is disabled when HAVE_TE is false (see the gating in comm_overlap where the code
checks elif not HAVE_TE), so include "TP overlap requires Transformer Engine
(HAVE_TE)". Keep the same YAML list style and place it alongside the existing TP
overlap constraints referencing tensor_model_parallel_size and
sequence_parallel.

---

Nitpick comments:
In `@skills/perf-techniques/cuda-graphs/SKILL.md`:
- Around line 217-221: Change the compound modifier "TE scoped graphs" to a
hyphenated form "TE-scoped graphs" in the paragraph discussing memory overhead
(the line that currently reads "TE scoped graphs add a few GB;"), so the
compound adjective is clear when used before the noun; update the occurrence(s)
of "TE scoped" to "TE-scoped" to maintain consistent style.

In `@skills/perf-techniques/sequence-packing/card.yaml`:
- Around line 39-50: The YAML uses prose placeholders inside scalar values
(e.g.,
recommended_path.llm_packed_sft.dataset.packed_sequence_specs.packed_sequence_size:
match_seq_length, recommended_path.vlm_in_batch_packing.train.micro_batch_size:
">1", and
recommended_path.cp_finetuning.dataset.packed_sequence_specs.pad_seq_to_mult: 2
* context_parallel_size); replace these pseudo-values with explicit,
machine-readable fields or structured constraints: for example add a constraint
object like packed_sequence_specs.packed_sequence_size_mode: "match_seq_length"
or packed_sequence_specs.packed_sequence_size_constraint: {mode:
"match_seq_length"}, replace the string range with a min/max field such as
vlm_in_batch_packing.train.micro_batch_size_min: 2, and replace arithmetic with
a factor field such as
cp_finetuning.dataset.packed_sequence_specs.pad_seq_to_mult_factor: 2 plus a
reference name context_parallel_size_variable so tooling can compute
pad_seq_to_mult at runtime—update llm_packed_sft, cp_finetuning, and
vlm_in_batch_packing accordingly so all values are explicit and
machine-readable.

In `@skills/resiliency/SKILL.md`:
- Around line 263-265: Replace the phrase "is not compatible with" with the more
concise "is incompatible with" in the bullet that begins "IPR + NeMo-Run" so the
line reads "IPR + NeMo-Run: In-process restart is incompatible with NeMo-Run or
Slurm preemption plugins." Keep the rest of the sentence (the note about
specific PyTorch/NCCL versions and env vars) unchanged; update only the quoted
wording in the SKILL.md bullet under "IPR + NeMo-Run".