「sam」の検索結果

Guildlines for handling json files

日本語の概要は準備中です。原文の説明を表示しています。

Guidelines for handling image files

日本語の概要は準備中です。原文の説明を表示しています。

Guidelines for handling text files

日本語の概要は準備中です。原文の説明を表示しています。

Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta), and scales from thousands to millions of rows. For small datasets (<10K rows), can optionally generate locally and upload to volumes. Use when user mentions 'synthetic data', 'test data', 'generate data', 'demo dataset', 'Faker', or 'sample data'.

日本語の概要は準備中です。原文の説明を表示しています。

Account assignment by revenue potential, geography, relationship. Workload balancing, TAM/SAM calculation, coverage models.

日本語の概要は準備中です。原文の説明を表示しています。

Define a product's motion design language -- duration and easing scales, choreography rules, and signature moves -- and export it as tokens plus ready-to-use Framer Motion variants and CSS. The difference between animations and a motion system: everything moves like it belongs to the same product.

日本語の概要は準備中です。原文の説明を表示しています。

TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.

日本語の概要は準備中です。原文の説明を表示しています。

Cleans up CRM data from HubSpot, Salesforce, Pipedrive, Zoho, Close, Attio, or any CRM CSV export. Finds duplicate contacts and companies with fuzzy matching (not just exact email), normalizes emails, phones to E.164, names, domains, states, and countries, flags stale, invalid, role, and test records, finds broken contact-company associations, and produces a reviewable merge plan plus import-ready files without touching the live CRM. Use this skill whenever the user wants to dedupe, find or merge duplicate contacts, merge companies or accounts, clean up a CRM, prep a CRM migration or re-import, or says the CRM export is a mess. Also use it when they mention only one symptom, like "the same person is in here three times", "half our leads are junk", or "our company records don't match".

日本語の概要は準備中です。原文の説明を表示しています。

Writes, explains, debugs, and optimizes BI calculations - Power BI / Fabric DAX measures and calculated columns, Tableau calculated fields (FIXED/INCLUDE/EXCLUDE LOD expressions, table calculations), and Looker LookML measures, dimensions, and derived tables. Use it whenever the request involves DAX, CALCULATE, a Power BI measure, a Tableau calc or LOD, LookML, or a business metric such as YoY, YTD, rolling 12 months, running total, percent of total, distinct customers, ranking, new vs returning customers, closing balances, or basket analysis. Use it especially when someone says a measure "shows the wrong total", "is blank", "ignores my slicer/filter", "repeats the same value on every row", or "is slow" - those are filter context, context transition, LOD order-of-operations, or fanout bugs this skill is built to diagnose. Produces the formula, the context it evaluates in, and a hand-checkable test with expected numbers.

日本語の概要は準備中です。原文の説明を表示しています。

Use to create or clean up the CLAUDE.md (or AGENTS.md) file that tells a coding agent how to work in a repo — commands, conventions, architecture, and the traps. Trigger when onboarding an agent to a codebase, when the agent keeps making the same repo-specific mistake, or when the user asks for project instructions, agent rules, or a context file.

日本語の概要は準備中です。原文の説明を表示しています。

API reference: HealthKit. Query for HKHealthStore, HKQuantitySample, workouts, health data read/write.

日本語の概要は準備中です。原文の説明を表示しています。

Extracts a user's writing voice from text samples via SICO comparative analysis. Use when building a voice profile for consistent generation.

日本語の概要は準備中です。原文の説明を表示しています。

Use when drafting an IRB or ethics research protocol. Writes Background, Study Design, Sample Size and Statistical Plan in full prose and leaves institution-specific sections as TODO skeletons. Filling an institutional Word form is /fill-protocol.

日本語の概要は準備中です。原文の説明を表示しています。

Use when choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.

日本語の概要は準備中です。原文の説明を表示しています。

Use when planning how many patients or cases a study needs before data collection (power analysis, IRB justification). Walks a decision tree to the right test and returns reproducible R/Python code and IRB-ready justification text. Analyzing collected data is /analyze-stats.

日本語の概要は準備中です。原文の説明を表示しています。

Score and compare covariance estimates with precise's assessor panel. Use when you need to judge an estimate out-of-sample or rank competing estimators — and especially in high dimensions, where the plain held-out likelihood is misleading.

日本語の概要は準備中です。原文の説明を表示しています。

Rigorously and honestly assess a NEW or proposed covariance / correlation / precision estimator, or a new covariance scoring rule, using precise. Use when someone proposes, asks to evaluate, or wants to compare a covariance methodology. Covers implementing it to the contract, conformance, benchmarking against the registry, out-of-sample validation, and statistically defensible inference.

日本語の概要は準備中です。原文の説明を表示しています。

Route Custom Diffusion workflows for concept data prep, diffusers training and SDXL, sample generation, delta tools, and CustomConcept101 evaluation.

日本語の概要は準備中です。原文の説明を表示しています。

Use audio-diffusion-pytorch for PyTorch waveform diffusion generators, text-conditioned audio generation, inpainting, upsampling, vocoding, and diffusion autoencoding.

日本語の概要は準備中です。原文の説明を表示しています。

Guides CUDA-based BigGAN-PyTorch training, checkpoint sampling, dataset preparation, metric preparation, model customization, and optional TensorFlow Hub weight conversion.

日本語の概要は準備中です。原文の説明を表示しています。

Router for Alpamayo R1 multimodal driving inference and trajectory sampling.

日本語の概要は準備中です。原文の説明を表示しています。

IDOR / BOLA hunting - two-account methodology, identifier discovery and UUID leak chaining, the trusted-identifier test, GraphQL node and nested-object IDOR, cross-tenant escalation, write and delete operations. Bounded ID sampling, never range sweeps. Wiki-first, FIND schema output. Trigger on IDOR, BOLA, broken access control, object level authorization, cross-tenant, "read another user's data", "swap the id", or any API path or parameter carrying a numeric ID, UUID, or account identifier.

日本語の概要は準備中です。原文の説明を表示しています。

Health check for the bb/pt/ctf workflow driver subsystem - verifies everything is in place so every machine runs the same. Checks vault-content consistency (scripts present, JSON valid, routing wired, all 69 tool pages carry phase:, the tool index resolves, the hook edits are in place) AND per-machine wiring (the three workflow skills symlinked, hooks registered, imports work), then runs a live init->board->next smoke test. Use when setting up the workflow on a new machine, after a vault sync, when the driver misbehaves, or on "bb-health", "campaign health", "is the workflow set up", "check hooks and scripts", "why is the board not working".

日本語の概要は準備中です。原文の説明を表示しています。

GraphQL IDOR/auth-bypass, XXE file-read/SSRF (SVG/DOCX/SAML), SSTI detection and RCE. OOB-mandatory for blind XXE. Wiki-first, FIND schema output.

日本語の概要は準備中です。原文の説明を表示しています。