WIP: Agent Skills Updates From Live Trials#1493
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📝 WalkthroughWalkthroughThis PR enhances evaluation workflows with improved quantization detection and baseline comparison requirements, standardizes task configurations into Markdown-based recipes with Python extraction helpers, introduces PTQ post-quantization validation gates, adds job monitoring via durable polling, and enables SLURM Quality of Service configuration support. ChangesEvaluation Workflow Enhancement
Task Recipe Standardization and Configuration Updates
PTQ Validation Framework
Monitoring, Baseline Verification, and Infrastructure
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Suggested reviewers
Important Pre-merge checks failedPlease resolve all errors before merging. Addressing warnings is optional. ❌ Failed checks (1 error, 1 inconclusive)
✅ Passed checks (4 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In @.claude/skills/monitor/SKILL.md:
- Around line 54-59: The documentation/logic currently enforces "report only
state changes" universally; update it so that user-initiated checks (e.g., when
the user explicitly asks "check status") return the full current status for each
job rather than only deltas—leave monitor-driven checks to still compare against
`last_status` in `.claude/active_jobs.json` and report only changes. Adjust the
wording and any associated pseudocode/implementation notes to branch on the
trigger type ("monitor output" vs "user-initiated") and on user-initiated flows
ensure you read the registry, check each job, return current state for each job,
and then update `last_status` accordingly. Ensure references to `last_status`
and `.claude/active_jobs.json` remain consistent so maintainers can find and
implement the conditional behavior.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (11)
.claude/skills/common/environment-setup.md.claude/skills/evaluation/SKILL.md.claude/skills/evaluation/tests/evals.json.claude/skills/launching-evals/references/analyze-results.md.claude/skills/monitor/SKILL.md.claude/skills/ptq/SKILL.md.claude/skills/ptq/references/checkpoint-validation.md.gitignoremodelopt/torch/quantization/model_quant.pytools/launcher/core.pytools/launcher/slurm_config.py
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #1493 +/- ##
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+ Coverage 76.79% 76.90% +0.11%
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Files 474 474
Lines 51560 51875 +315
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+ Hits 39593 39893 +300
- Misses 11967 11982 +15
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Actionable comments posted: 2
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⚠️ Outside diff range comments (1)
.claude/skills/evaluation/SKILL.md (1)
203-212:⚠️ Potential issue | 🟠 Major | ⚡ Quick winFix task snippet schema mismatch (
tasksvsevaluation.tasks).The Step 5 example contradicts earlier instructions to edit
evaluation.tasks. Keepingtasks:here can make generated configs invalid or ignored.Suggested fix
- tasks: - - name: <task> - nemo_evaluator_config: - config: - params: - temperature: <value> - max_new_tokens: <value> - ... + evaluation: + tasks: + - name: <task> + nemo_evaluator_config: + config: + params: + temperature: <value> + max_new_tokens: <value> + ...🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.claude/skills/evaluation/SKILL.md around lines 203 - 212, The YAML example uses a top-level "tasks:" key which conflicts with the expected "evaluation.tasks" namespace; update the snippet so the tasks list is nested under "evaluation.tasks" (e.g., replace "tasks:" with "evaluation.tasks:" and keep the existing task entries like "name" and "nemo_evaluator_config" intact), and verify any references to "tasks" in the surrounding text or examples are corrected to "evaluation.tasks" to keep schema consistent.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In @.claude/skills/evaluation/recipes/tasks/gpqa.md:
- Around line 73-75: The extractor extract_gpqa_score currently can raise
IndexError when called without args and uses raw open(...) with yaml.safe_load;
add basic argument validation (ensure path is provided and repeats, if given, is
an int) and use a safe file context (with open(path, "r") as f) and
yaml.safe_load(f) while catching FileNotFoundError and yaml.YAMLError and
re-raising a clear ValueError; also validate that the expected keys exist in the
loaded dict (results -> groups -> gpqa -> metrics) and raise ValueError if
missing. Apply the same validation and safe-loading pattern to the similar
extractor function around lines 94-97 to ensure consistent error handling.
In @.claude/skills/evaluation/recipes/tasks/scicode.md:
- Around line 105-108: The extract_score function currently assumes a valid path
and opens the YAML without a context manager; fix it by validating the path
argument (raise ValueError or return a clear error if path is falsy), check the
file exists (catch FileNotFoundError), and read the YAML using a context manager
(with open(path) as f: data = yaml.safe_load(f)); then safely access
TASKS[group] and data["results"]["groups"][group"]["metrics"] (use .get or catch
KeyError to provide a clearer error). Apply the same changes to the other
identical snippet that reads the YAML and accesses metrics.
---
Outside diff comments:
In @.claude/skills/evaluation/SKILL.md:
- Around line 203-212: The YAML example uses a top-level "tasks:" key which
conflicts with the expected "evaluation.tasks" namespace; update the snippet so
the tasks list is nested under "evaluation.tasks" (e.g., replace "tasks:" with
"evaluation.tasks:" and keep the existing task entries like "name" and
"nemo_evaluator_config" intact), and verify any references to "tasks" in the
surrounding text or examples are corrected to "evaluation.tasks" to keep schema
consistent.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (18)
.claude/skills/evaluation/SKILL.md.claude/skills/evaluation/recipes/examples/example_eval.yaml.claude/skills/evaluation/recipes/tasks/aime2025.md.claude/skills/evaluation/recipes/tasks/aime2025.yaml.claude/skills/evaluation/recipes/tasks/gpqa.md.claude/skills/evaluation/recipes/tasks/gpqa.yaml.claude/skills/evaluation/recipes/tasks/ifbench.md.claude/skills/evaluation/recipes/tasks/ifbench.yaml.claude/skills/evaluation/recipes/tasks/livecodebench.md.claude/skills/evaluation/recipes/tasks/livecodebench.yaml.claude/skills/evaluation/recipes/tasks/mmlu_pro.md.claude/skills/evaluation/recipes/tasks/mmlu_pro.yaml.claude/skills/evaluation/recipes/tasks/scicode.md.claude/skills/evaluation/recipes/tasks/scicode.yaml.claude/skills/evaluation/tests/evals.json.claude/skills/ptq/SKILL.md.claude/skills/ptq/references/checkpoint-validation.md.claude/skills/ptq/tests.json
💤 Files with no reviewable changes (6)
- .claude/skills/evaluation/recipes/tasks/ifbench.yaml
- .claude/skills/evaluation/recipes/tasks/mmlu_pro.yaml
- .claude/skills/evaluation/recipes/tasks/aime2025.yaml
- .claude/skills/evaluation/recipes/tasks/scicode.yaml
- .claude/skills/evaluation/recipes/tasks/gpqa.yaml
- .claude/skills/evaluation/recipes/tasks/livecodebench.yaml
✅ Files skipped from review due to trivial changes (3)
- .claude/skills/evaluation/recipes/examples/example_eval.yaml
- .claude/skills/evaluation/recipes/tasks/ifbench.md
- .claude/skills/evaluation/recipes/tasks/mmlu_pro.md
🚧 Files skipped from review as they are similar to previous changes (1)
- .claude/skills/evaluation/tests/evals.json
| def extract_gpqa_score(path, repeats=None): | ||
| data = yaml.safe_load(open(path)) | ||
| metrics = data["results"]["groups"]["gpqa"]["metrics"] |
There was a problem hiding this comment.
Add basic argument validation and safe file loading in the extractor.
This snippet can throw IndexError if invoked without args and should avoid raw open(...) in yaml.safe_load.
Suggested fix
def extract_gpqa_score(path, repeats=None):
- data = yaml.safe_load(open(path))
+ with open(path, "r", encoding="utf-8") as f:
+ data = yaml.safe_load(f)
@@
if __name__ == "__main__":
- path = sys.argv[1]
+ if len(sys.argv) < 2:
+ raise SystemExit("Usage: python extract_gpqa_score.py <results.yaml> [repeats]")
+ path = sys.argv[1]
repeats = int(sys.argv[2]) if len(sys.argv) > 2 else None
print(extract_gpqa_score(path, repeats))Also applies to: 94-97
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In @.claude/skills/evaluation/recipes/tasks/gpqa.md around lines 73 - 75, The
extractor extract_gpqa_score currently can raise IndexError when called without
args and uses raw open(...) with yaml.safe_load; add basic argument validation
(ensure path is provided and repeats, if given, is an int) and use a safe file
context (with open(path, "r") as f) and yaml.safe_load(f) while catching
FileNotFoundError and yaml.YAMLError and re-raising a clear ValueError; also
validate that the expected keys exist in the loaded dict (results -> groups ->
gpqa -> metrics) and raise ValueError if missing. Apply the same validation and
safe-loading pattern to the similar extractor function around lines 94-97 to
ensure consistent error handling.
| def extract_score(path, group="scicode"): | ||
| spec = TASKS[group] | ||
| data = yaml.safe_load(open(path)) | ||
| metrics = data["results"]["groups"][group]["metrics"] |
There was a problem hiding this comment.
Harden CLI/file handling in the score extractor snippet.
The snippet crashes with IndexError when no path is passed, and it opens the YAML file without a context manager.
Suggested fix
def extract_score(path, group="scicode"):
spec = TASKS[group]
- data = yaml.safe_load(open(path))
+ with open(path, "r", encoding="utf-8") as f:
+ data = yaml.safe_load(f)
@@
if __name__ == "__main__":
- path = sys.argv[1]
+ if len(sys.argv) < 2:
+ raise SystemExit("Usage: python extract_score.py <results.yaml> [scicode|gpqa]")
+ path = sys.argv[1]
group = sys.argv[2] if len(sys.argv) > 2 else "scicode"
print(extract_score(path, group))Also applies to: 135-138
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In @.claude/skills/evaluation/recipes/tasks/scicode.md around lines 105 - 108,
The extract_score function currently assumes a valid path and opens the YAML
without a context manager; fix it by validating the path argument (raise
ValueError or return a clear error if path is falsy), check the file exists
(catch FileNotFoundError), and read the YAML using a context manager (with
open(path) as f: data = yaml.safe_load(f)); then safely access TASKS[group] and
data["results"]["groups"][group"]["metrics"] (use .get or catch KeyError to
provide a clearer error). Apply the same changes to the other identical snippet
that reads the YAML and accesses metrics.
There was a problem hiding this comment.
Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In @.claude/skills/evaluation/SKILL.md:
- Around line 260-267: The preflight check currently tests for any credential
entry using the generic grep command; change it to verify credentials per
registry host used by the selected images by searching for the specific registry
hostnames (not just any "machine" entry) in ~/.config/enroot/.credentials.
Update the documented check (the grep invocation shown) to demonstrate matching
the actual registry host(s) (e.g., loop or run grep for each selected image's
registry host) so the preflight returns true only when credentials exist for
those specific hosts.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
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Review profile: CHILL
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📒 Files selected for processing (7)
.claude/skills/evaluation/SKILL.md.claude/skills/evaluation/recipes/env.example.claude/skills/evaluation/recipes/tasks/aa_lcr.md.claude/skills/evaluation/recipes/tasks/aime2025.md.claude/skills/evaluation/recipes/tasks/hle_aa.md.claude/skills/evaluation/recipes/tasks/ifbench.md.claude/skills/evaluation/recipes/tasks/mmlu_pro_aa_v3.md
✅ Files skipped from review due to trivial changes (6)
- .claude/skills/evaluation/recipes/env.example
- .claude/skills/evaluation/recipes/tasks/mmlu_pro_aa_v3.md
- .claude/skills/evaluation/recipes/tasks/aa_lcr.md
- .claude/skills/evaluation/recipes/tasks/hle_aa.md
- .claude/skills/evaluation/recipes/tasks/ifbench.md
- .claude/skills/evaluation/recipes/tasks/aime2025.md
| ```bash | ||
| ssh <host> "grep -E '^\s*machine\s+' ~/.config/enroot/.credentials 2>/dev/null" | ||
| ``` | ||
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||
| **Decision flow (check before submitting):** | ||
| 1. Check if the cluster has credentials for the default DockerHub image (see command above) | ||
| 2. If DockerHub credentials exist → use the default image and submit | ||
| 3. If DockerHub credentials are missing but can be added → add them (see `slurm-setup.md` section 6), then submit | ||
| 4. If DockerHub credentials cannot be added → override `deployment.image` to the NGC alternative and submit: | ||
| 1. If the selected images are public → submit without an auth preflight | ||
| 2. If any selected image is private or access-restricted → check for credentials for that image's registry (see command above) | ||
| 3. If credentials exist → use the selected image and submit |
There was a problem hiding this comment.
Make credential verification registry-specific.
Line 261 currently checks whether any credential entry exists, not whether credentials exist for the selected registry host(s). That can pass preflight but still fail image pulls.
Suggested doc fix
-ssh <host> "grep -E '^\s*machine\s+' ~/.config/enroot/.credentials 2>/dev/null"
+ssh <host> "awk '/^\s*machine\s+/ {print $2}' ~/.config/enroot/.credentials 2>/dev/null"
+# Verify the required registry host(s) from selected images are present (e.g., docker.io, nvcr.io, registry.internal).🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In @.claude/skills/evaluation/SKILL.md around lines 260 - 267, The preflight
check currently tests for any credential entry using the generic grep command;
change it to verify credentials per registry host used by the selected images by
searching for the specific registry hostnames (not just any "machine" entry) in
~/.config/enroot/.credentials. Update the documented check (the grep invocation
shown) to demonstrate matching the actual registry host(s) (e.g., loop or run
grep for each selected image's registry host) so the preflight returns true only
when credentials exist for those specific hosts.
There was a problem hiding this comment.
Actionable comments posted: 1
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
.claude/skills/evaluation/recipes/tasks/tau2_bench_telecom.md (1)
38-39:⚠️ Potential issue | 🟠 Major | ⚡ Quick winComplete the Score Extraction section.
The Score Extraction section contains only a header with no content. Users need guidance on how to extract and interpret the
pass_1metric for this task. Please add content similar to other task recipes (e.g., AIME 2025, GPQA) that explains which metric to use and how to extract it from the evaluation results.Do you want me to help draft the score extraction guidance based on the primary metric
pass_1and the tau2_bench harness documentation?🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.claude/skills/evaluation/recipes/tasks/tau2_bench_telecom.md around lines 38 - 39, The Score Extraction section is empty—add a short paragraph stating that the primary metric is pass_1 and instruct users to extract the pass_1 value from the tau2_bench evaluation results (e.g., from the metrics or results JSON under the "pass_1" key), report it as a percentage (multiply by 100 if the harness returns a fraction), and include any aggregation used (mean across seeds or runs). Reference the task name tau2_bench_telecom and the harness docs for exact JSON field names and show that the reported score should be the aggregated pass_1 value used for comparisons.
♻️ Duplicate comments (1)
.claude/skills/evaluation/SKILL.md (1)
260-262:⚠️ Potential issue | 🟡 Minor | ⚡ Quick winMake credential verification registry-specific.
The grep command checks for any credential entry, not credentials for the specific registry host(s) used by the selected images. This can pass the preflight but still fail image pulls if credentials for the required registries are missing.
📝 Suggested fix
-ssh <host> "grep -E '^\s*machine\s+' ~/.config/enroot/.credentials 2>/dev/null" +ssh <host> "awk '/^\s*machine\s+/ {print $2}' ~/.config/enroot/.credentials 2>/dev/null" +# Verify the required registry host(s) from selected images are present (e.g., docker.io, nvcr.io, registry.internal).🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.claude/skills/evaluation/SKILL.md around lines 260 - 262, The current preflight uses the command string ssh <host> "grep -E '^\s*machine\s+' ~/.config/enroot/.credentials 2>/dev/null" which only checks for any credential entry; change it to verify registry-specific credentials by extracting registry hostnames from the selected images and running grep for each host (e.g., grep -E "^\s*machine\s+<registryHost>\b" ~/.config/enroot/.credentials) or equivalent per-host checks over SSH; update the code that emits the ssh grep command in SKILL.md to iterate the image registry list and fail the preflight if any registryHost lookup returns no match.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In @.claude/skills/evaluation/SKILL.md:
- Around line 59-68: Update the ambiguous phrase "Do Step 3, Step 4, then Step
7.5/8" in the SKILL.md shortcut section to explicitly state which Step 8
substeps apply; replace it with something like "Do Step 3, Step 4, Step 7.5,
then Step 8 (complete the applicable substeps 8.1/8.2/8.3)" or "Do Step 3, Step
4, Step 7.5, then Step 8.1–8.3 as applicable" so readers aren’t confused by the
restructured Step 8; locate the exact string "Do Step 3, Step 4, then Step
7.5/8" and update it accordingly.
---
Outside diff comments:
In @.claude/skills/evaluation/recipes/tasks/tau2_bench_telecom.md:
- Around line 38-39: The Score Extraction section is empty—add a short paragraph
stating that the primary metric is pass_1 and instruct users to extract the
pass_1 value from the tau2_bench evaluation results (e.g., from the metrics or
results JSON under the "pass_1" key), report it as a percentage (multiply by 100
if the harness returns a fraction), and include any aggregation used (mean
across seeds or runs). Reference the task name tau2_bench_telecom and the
harness docs for exact JSON field names and show that the reported score should
be the aggregated pass_1 value used for comparisons.
---
Duplicate comments:
In @.claude/skills/evaluation/SKILL.md:
- Around line 260-262: The current preflight uses the command string ssh <host>
"grep -E '^\s*machine\s+' ~/.config/enroot/.credentials 2>/dev/null" which only
checks for any credential entry; change it to verify registry-specific
credentials by extracting registry hostnames from the selected images and
running grep for each host (e.g., grep -E "^\s*machine\s+<registryHost>\b"
~/.config/enroot/.credentials) or equivalent per-host checks over SSH; update
the code that emits the ssh grep command in SKILL.md to iterate the image
registry list and fail the preflight if any registryHost lookup returns no
match.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
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📒 Files selected for processing (13)
.claude/skills/evaluation/SKILL.md.claude/skills/evaluation/recipes/env.example.claude/skills/evaluation/recipes/examples/example_eval.yaml.claude/skills/evaluation/recipes/tasks/aa_lcr.md.claude/skills/evaluation/recipes/tasks/aime2025.md.claude/skills/evaluation/recipes/tasks/gpqa.md.claude/skills/evaluation/recipes/tasks/hle_aa_v2.md.claude/skills/evaluation/recipes/tasks/ifbench.md.claude/skills/evaluation/recipes/tasks/livecodebench.md.claude/skills/evaluation/recipes/tasks/mmlu_pro.md.claude/skills/evaluation/recipes/tasks/mmmu_pro.md.claude/skills/evaluation/recipes/tasks/scicode.md.claude/skills/evaluation/recipes/tasks/tau2_bench_telecom.md
✅ Files skipped from review due to trivial changes (6)
- .claude/skills/evaluation/recipes/tasks/mmmu_pro.md
- .claude/skills/evaluation/recipes/tasks/hle_aa_v2.md
- .claude/skills/evaluation/recipes/tasks/ifbench.md
- .claude/skills/evaluation/recipes/tasks/mmlu_pro.md
- .claude/skills/evaluation/recipes/tasks/livecodebench.md
- .claude/skills/evaluation/recipes/tasks/aa_lcr.md
🚧 Files skipped from review as they are similar to previous changes (4)
- .claude/skills/evaluation/recipes/env.example
- .claude/skills/evaluation/recipes/tasks/gpqa.md
- .claude/skills/evaluation/recipes/examples/example_eval.yaml
- .claude/skills/evaluation/recipes/tasks/scicode.md
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Signed-off-by: Chad Voegele <cvoegele@nvidia.com>
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Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Chad Voegele <cvoegele@nvidia.com>
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| Prefer the `pass@1[avg-of-N]` metric matching the configured repeat count. | ||
| If the repeat count is unknown, use the highest available `avg-of-N`. | ||
|
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||
| ```python |
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qq why we still need these python code here?
What does this PR do?
Type of change: bug fix
Usage
Ask Claude Code:
Testing
I'm running the full loop with the above prompt, and iterating on skills to resolve undesired agent behavior.
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git commit -s -S).Make sure you read and follow the Security Best Practices (e.g. avoiding hardcoded
trust_remote_code=True,torch.load(..., weights_only=False),pickle, etc.).CONTRIBUTING.md: ✅Additional Information
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Summary by CodeRabbit
Release Notes
New Features
Documentation
Tests