Use when deeply analyzing a single paper and producing structured notes on claims, methods, figures, evaluation, strengths, limitations, and related work.
لغة النص الأصلي: الإنجليزية
القائمة
Skills في هذا المستودع
جمع SkillsMP عدد ١٨٤ من skills من jluo41/Tools. افتح أي skill لمراجعة مصدره وتفاصيله.
jluo41/Toolsعرض ٤٠ من أصل ١٨٤ skills مجمعة.
Use when deeply analyzing a single paper and producing structured notes on claims, methods, figures, evaluation, strengths, limitations, and related work.
لغة النص الأصلي: الإنجليزية
Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue…
لغة النص الأصلي: الإنجليزية
Use when conducting literature reviews, summarizing papers, comparing methodologies, identifying research gaps, or supporting scholarly writing across disciplines.
لغة النص الأصلي: الإنجليزية
Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY,…
لغة النص الأصلي: الإنجليزية
Review type specialist for the discovery layer: analyze across sources — judge a claim (prior_art_check / counterevidence -> verdict.md) or map a field (landscape_review / benchmark_landscape -> landscape.md). Dispatches research-lit / comm-lit-review /…
لغة النص الأصلي: الإنجليزية
Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.
لغة النص الأصلي: الإنجليزية
Idea type specialist for the discovery layer: the ideation loop — generate + rank candidate claims (idea_generation -> ideas.md) and evaluate their novelty (novelty_check -> verdict.md). Dispatches idea-creator and novelty-check. Trigger: generate ideas,…
لغة النص الأصلي: الإنجليزية
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
لغة النص الأصلي: الإنجليزية
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
لغة النص الأصلي: الإنجليزية
External-evidence layer, and one of the two EXECUTORS (task is the other — same shape, same rules). One research topic = one discovery-folder running Plan -> Build(opt) -> Execute -> Report, typed Search | Review | Idea; buckets 1_search/2_review/3_idea are…
لغة النص الأصلي: الإنجليزية
Read-only specialist for haipipe-project. Reviews project structure, summarizes, generates inventory, prints overview. Touches no files. Called by /haipipe-project orchestrator. Direct invocation works for project audit work.
لغة النص الأصلي: الإنجليزية
Modify specialist for haipipe-project. Reorganizes files to fix structural violations: flatten flat tasks into groups, rename mis-numbered task folders, align Track A code with Track B examples, fix broken paired-example references. Called by /haipipe-project…
لغة النص الأصلي: الإنجليزية
Stage 4 (AIData) specialist: builds/runs/reviews TfmFn / SplitFn, inspects 4-AIDataStore, loads AIData-layer assets + tensors, merges multi-partition CaseSets via streaming HF Dataset. Called by /haipipe-data; direct invocation works stage-scoped.
لغة النص الأصلي: الإنجليزية
Stage 3 (Case) specialist: builds/runs/reviews TriggerFn / CaseFn, inspects 3-CaseStore, loads case-layer assets, runs multi-partition in parallel (embarrassingly parallel). Called by /haipipe-data; direct invocation works stage-scoped.
لغة النص الأصلي: الإنجليزية
External-reference specialist: builds/runs/reviews ExternalFn (e_build_external_*.py), inspects ExternalStore, loads dimension + engagement assets, previews joins into Source/Record sets. Called by /haipipe-data (recommended entry); direct invocation works…
لغة النص الأصلي: الإنجليزية
Stage 0' (raw cohort) specialist: builds a business-readable picture of how one data point in a raw cohort extract is generated, BEFORE it enters Stage 1 (Source). Trigger: raw, rawstore, 0-rawstore, raw cohort, data point generation, datapoint timeline,…
لغة النص الأصلي: الإنجليزية
Stage 2 (Record) specialist: builds/runs/reviews HumanFn / RecordFn, inspects 2-RecStore, loads record-layer assets, supports multi-partition via patient_ids predicate pushdown. Called by /haipipe-data; direct invocation works stage-scoped.
لغة النص الأصلي: الإنجليزية
Cross-stage transport specialist: pushes/pulls cohort assets between local _WorkSpace and the configured remote (S3 / GCS / Databricks / Google Drive) via hai-remote-sync; never destructive. Trigger: push, pull, sync, remote, S3, upload, download, fetch,…
لغة النص الأصلي: الإنجليزية
Run any Stage 1-4 data pipeline work: parses intent (stage + function) and dispatches to the right specialist (source/record/case/aidata, plus raw/external/remote). Use for SourceFn/RecordFn/CaseFn/TfmFn/SplitFn builds, runs, dashboards, reviews, or any…
لغة النص الأصلي: الإنجليزية
Stage 1 (Source) specialist: builds/runs/reviews SourceFn, inspects 1-SourceStore, loads source-layer typed frames. Called by /haipipe-data (recommended entry); direct invocation works stage-scoped.
لغة النص الأصلي: الإنجليزية
data-pipeline task-folder specialist: scaffolds AND executes {NN}_<name>/ task-folders that run Stage 1-4 builders (Source/Record/Case/AIData) with multi-partition support. Called by /haipipe-task when task-type=data. Cross-references /haipipe-data for Fn…
لغة النص الأصلي: الإنجليزية
Raw extraction task-folder specialist: scaffolds {NN}_<name>/ task-folders in the raw-extraction task-group (default R-series). Two patterns: extract-wide-process-local (Databricks -> parquet -> local Python; non-PHI) and server-resident (all-Spark pipeline…
لغة النص الأصلي: الإنجليزية
Layer 1 (Algorithm) specialist of haipipe-nn: defines the algorithm contract (model class, forward pass, loss, metric). Covers mlpredictor, tsforecast, tefm, tediffusion, bandit. Called by /haipipe-nn; direct invocation works layer-scoped.
لغة النص الأصلي: الإنجليزية
Layer 3 (Instance) specialist of haipipe-nn: materializes a trained ModelInstance by driving its Tuners (registry create -> fit -> save_model). Called by /haipipe-nn; direct invocation works layer-scoped.
لغة النص الأصلي: الإنجليزية
Layer 4 (ModelSet / Pipeline) specialist of haipipe-nn: composes multiple ModelInstances into a registry-backed pipeline. Called by /haipipe-nn; direct invocation works layer-scoped.
لغة النص الأصلي: الإنجليزية
Run any Stage 5 NN pipeline work: parses intent (layer + function) and dispatches to the right specialist (algo/tuner/instance/modelset). Use for algorithms (mlpredictor/tsforecast/tefm/tediffusion/bandit), tuner sweeps, ModelInstance materialization,…
لغة النص الأصلي: الإنجليزية
Layer 2 (Tuner) specialist of haipipe-nn: defines the hyperparameter search space and the tuner that drives sweeps. Called by /haipipe-nn; direct invocation works layer-scoped.
لغة النص الأصلي: الإنجليزية
algo-dev task-folder specialist: scaffolds {NN}_<name>/ task-folders in the algo-dev task-group (default X_algo) that smoke-test a newly developed algorithm class end-to-end on a TINY config. NOT full training -- see /haipipe-task-for-fit. Called by…
لغة النص الأصلي: الإنجليزية
Databricks Model Serving deploy specialist for haipipe-end: wraps an Endpoint_Set into MLflow pyfunc + Unity Catalog model, deploys to Databricks Model Serving, runs live smoke tests, monitors, tears down. Reads (never modifies) Endpoint_Sets from…
لغة النص الأصلي: الإنجليزية
Local self-hosted deploy specialist for haipipe-end: wraps an Endpoint_Set into a local HTTP server -- Flask (default), FastAPI, or local Docker container -- for dev, integration testing, demos, and DIY deployments. Reads (never modifies) Endpoint_Sets from…
لغة النص الأصلي: الإنجليزية
MLflow deploy specialist for haipipe-end. STATUS: DEFERRED -- no platform-mlflow-inference repo backs it yet; placeholder. Would register an Endpoint_Set into an MLflow Model Registry and serve via `mlflow models serve`. Reads (never modifies) Endpoint_Sets…
لغة النص الأصلي: الإنجليزية
AWS SageMaker deploy specialist for haipipe-end: wraps an Endpoint_Set into SageMaker model.tar.gz, deploys to a SageMaker endpoint, runs live smoke tests, monitors logs, tears down. Reads (never modifies) Endpoint_Sets from haipipe-end-endpointset. Read the…
لغة النص الأصلي: الإنجليزية
Databricks develop specialist for haipipe-end. STATUS: DEFERRED -- backing repo platforms/platform-databrick-training/ exists but this skill isn't wired to it yet. Would run Stage 5 training as a Databricks Job with model logged to Unity Catalog and exported…
لغة النص الأصلي: الإنجليزية
Local develop specialist for haipipe-end: runs Stage 5 training on the local machine and produces an Endpoint_Set under 6-EndpointStore/, for dev iteration, smoke tests, and DIY builds. Mostly delegates to /haipipe-nn modelset for training; exists for…
لغة النص الأصلي: الإنجليزية
AWS SageMaker develop specialist for haipipe-end: runs Stage 5 training as a managed SageMaker Pipeline (Preprocess -> Train -> Reorganize -> RegisterModel) and produces a deployable Endpoint_Set / registered model package. Writes Endpoint_Sets that…
لغة النص الأصلي: الإنجليزية
Endpoint_Set artifact-as-whole specialist: target-agnostic operations on the deployable artifact -- package (Stage 5 -> 6), local inference() smoke test, structural review, dashboard. Per-Fn-type design/review lives in…
لغة النص الأصلي: الإنجليزية
Input2SrcFn specialist -- designs/reviews the wire-payload->record function in an Endpoint_Set (deserializes a JSON request into a ProcessedDF row). Platform-specific: one impl per deploy platform (SageMaker flat JSON vs Databricks dataframe_records);…
لغة النص الأصلي: الإنجليزية
MetaFn specialist -- designs/reviews the model-metadata-lookup function in an Endpoint_Set. One of 5 inference Fn-types. Called by /haipipe-end when intent references MetaFn, model metadata, model card, or `meta`.
لغة النص الأصلي: الإنجليزية
TrigFn specialist -- designs/reviews the trigger-detection function in an Endpoint_Set. One of 5 inference Fn-types. Called by /haipipe-end when intent references TrigFn, trigger detection, or `trig`.
لغة النص الأصلي: الإنجليزية
endpoint task-folder specialist: scaffolds AND executes {NN}_<name>/ task-folders that package a trained ModelInstance_Set into a deployable Endpoint_Set (Stage 6) via c_endpoint_nb.py. Called by /haipipe-task when task-type=endpoint. Cross-references…
لغة النص الأصلي: الإنجليزية