「sam」の検索結果

Identifies young patients with classic primary aldosteronism features who may proceed directly to unilateral adrenalectomy without adrenal venous sampling based on high probability of unilateral disease. Triggered when a clinician sees a patient <35 years with hypokalemia, unilateral adrenal tumor on CT, and high plasma aldosterone concentration and asks whether AVS can be bypassed.

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Determines whether adrenal venous sampling (AVS) is needed in addition to CT for lateralizing primary aldosteronism before surgery. Trigger phrases include "patient with primary aldosteronism considering surgery", "unilateral adrenal adenoma on CT", "surgical candidate", and "age <35 with hypokalemia and >1‑cm adenoma".

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Determines when adrenal venous sampling may be skipped in primary aldosteronism. Applies to patients <35 years with spontaneous hypokalemia, marked aldosterone excess, and unilateral adrenal lesions suggestive of cortical adenoma on CT.

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Interprets the saline infusion test (SIT) to assess the probability of primary aldosteronism when a patient has a positive aldosterone-to-renin ratio (ARR) and requires confirmatory testing. Triggers include evaluating post‑infusion plasma aldosterone concentration (PAC) after a positive ARR, hypertension work‑up, or when deciding whether to proceed to adrenal venous sampling (AVS).

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Determines whether to perform adrenal venous sampling (AVS) to lateralize aldosterone excess in patients with confirmed primary aldosteronism (PA) who are being evaluated for surgical treatment. Indicated when surgery is feasible and desired by the patient, or when subtype workup is planned for a surgical candidate, especially in those younger than 35 years with spontaneous hypokalemia, marked aldosterone excess, and unilateral adrenal lesions on CT.

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Reconcile baseline-versioned files that the `create-baseline upgrade` CLI staged for LLM-assisted semantic merge. Use when the CLI prints "Open Claude Code and run /upgrade-project to reconcile". Reads the stage manifest at `.claude/state/upgrade/<ts>/manifest.json`, reasons through each pending file's three-way delta in main context, writes a reconciled LOCAL, then deletes the stage when every file lands. Supports `--dry-run` (preview the reconciled diff without writing) and a structured "needs-user-input" fallback when the conflict cannot be disambiguated automatically.

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Preflight a spec draft without saving. Runs the same checks as the write-boundary hooks — PlantUML syntax, required diagram presence, AC-to-sequence traceability, Design calls quality floor, and System delta row resolution — and prints a compact pass/fail table. Use while iterating so the hooks don't bite on save.

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Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

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Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).

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Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

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Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

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Find Amazon Ads search terms ready for exact-match harvesting from auto, broad, phrase, or other discovery campaigns. Use when Codex needs standalone or Rocketcart MCP-aware search-term harvesting: classify terms by harvest readiness, resolve live IDs, choose safe destination campaigns/ad groups, preflight duplicates/current negatives/destination feasibility, decide whether source negatives are justified, execute only explicitly approved rows, and read back/monitor Sponsored Products or Sponsored Brands actions without unsafe negatives, duplicate routing, stale approvals, brand-defense cuts, own-ASIN-defense cuts, launch/rank mistakes, or low-sample overfitting.

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The original reddapi.dev Reddit search skill (vector search, semantic search, trends, subreddit discovery), no Reddit OAuth or app registration needed. This is the same engine now packaged as reddit-research with added market-research playbooks and a fuller pitch on semantic vs keyword search; reddapi is kept live under its original name for existing installs and works standalone. Use when the user says 'reddapi' by name, or wants a minimal drop-in Reddit search skill without the extra research-workflow guidance. For the expanded research-oriented version with query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads. For a bare API reference, see reddit-search-api.

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SAM: zero-shot image segmentation via points, boxes, masks.

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Splits scarce time, budget or traffic across competing products, channels, campaigns or variants by treating them as a multi-armed bandit - Thompson sampling over beta posteriors, with optimism for anything not yet tried enough to judge. Use when deciding what to work on next, how to divide a marketing budget, which product to prioritise, whether to kill something that is underperforming, or when picking a winner among test variants.

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Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.

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Generate the ≤10-minute Loom walkthrough script for a completed Weekly Community Signal report — a plain spoken briefing that dives straight into what the team needs to know, walking the report top to bottom (CopilotKit page first, then AG-UI in the same order). Straightforward and factual, NOT a radio show or a performance; no hype opener, no blame framing. Runs after every report (invoked by weekly-report) and on "loom script", "walkthrough script", "record the loom", "narrate the report".

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Expert-level probability theory knowledge. Use when working with probability spaces, random variables, distributions, expectation, variance, conditional probability, stochastic processes, Markov chains, martingales, or measure-theoretic probability. Also use when the user mentions 'sample space', 'random variable', 'expected value', 'variance', 'conditional probability', 'independence', 'Markov chain', 'Poisson process', 'moment generating function', 'law of large numbers', 'central limit theorem', or 'stochastic process'.

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Expert-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling distribution'.

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Test, fold or refute hypotheses beside the knowledge record, and reconcile records across branches. Use when open or check say hypotheses wait or an id is CONTESTED, when a write was refused into a hypothesis, before merging a branch whose record changed, and when a pull request's dry run or remeasure is red. Covers consolidate --dry-run, the fold, --refute, --from, same and distinct at the fold, and remeasure.

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Write what the work found into the project's knowledge record, so the next session inherits it instead of re-deriving it. Use the moment something worth keeping exists: a fact taken from a source, a rule worked out, a decision or conclusion, a measurement, a correction to a recorded value, or a question left open - and check for unrecorded findings before implementation, handoff (including a PR), or finishing work. Record within the user's write authorization. The first write creates GROUNDING.yaml. Covers one-report update, add, set, review, same and distinct, judgments with a falsifier, and background capture.

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Read-only SRE checkup of any GCP project: deterministic probes of the edge, Cloud Run services, 7-day error logs, Cloud Scheduler, alert policies and uptime checks, Secret Manager and IAM, the data stores and the machine's own scheduled jobs, audited into one fixed status table (LIVE / WARNING / RED / INCONCLUSIVE) with evidence, findings by severity, what could not be checked, and a single OVERALL line delivered as one notification. Parametrised by a per-project manifest, so the same routine runs on every project. Use when the operator says "cloud checkup", "SRE check", "is everything live", "what's healthy / warning / red", "any errors this week", "audit the infra", "weekly checkup", "set up the weekly checkup", before a deploy or demo, or after an incident. Cloud Run first; App Engine and GKE differ only in the serving probes.

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Use when a character must stay visually identical across AI video scenes — locks identity tokens (silhouette, palette, wardrobe, prop) in JSON. Triggers 'character lock', 'same character'.

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Agents work in parallel on the same task; judges evaluate and select the winner.

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。