「diagnostic」の検索結果

Decompose substantive work into phases, dispatch each phase to a sub-agent, and adjudicate what comes back. Use whenever a request asks for implementation, investigation, a fix, a review, or any change to files — including small ones — and whenever you are about to read source or run a diagnostic yourself instead of handing it off. Also use when a report from a sub-agent needs judging, when a phase needs re-dispatching, or when a user names one instance of a pattern. Does not apply when your own prompt begins "Your ROLE_TYPE is sub-agent." — then follow references/sub-agent-contract.md instead.

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A diagnostic tool for OpenClaw agents -- checks skill registry connectivity, AGENTS.md setup, config file validity, and installed skill health. Use when your setup seems broken, skills aren't loading, or you want to audit your agent's configuration.

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。

Manage Alibaba Cloud Elastic Compute Service (ECS) using the @alicloud/ecs20140526 TypeScript SDK. Use when working with cloud servers on Alibaba Cloud, including instance lifecycle (create, start, stop, reboot, delete), disks and snapshots, images, security groups, VPC networking, EIP, ENI, SSH key pairs, dedicated hosts, auto provisioning, launch templates, Cloud Assistant commands, tags, system events, diagnostics, storage capacity units, and prefix lists. Covers all 374 APIs of the ECS 20140526 version.

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。

OCRs scanned or image-only corpora with vision-language models in three phases. Evaluate selects a system by measured CER or WER against stratified human ground truth. Run builds the production pipeline. Clean corrects raw OCR with LLM and rule-based passes, quality diagnostics, and span-level provenance. Use when choosing an OCR model for a corpus, measuring OCR accuracy, transcribing scans at scale, or correcting raw OCR. Born-digital documents with text layers go to doc-to-markdown.

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。

Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design, estimation, measurement error, external validity, and interpretation. Use when checking whether a conjoint design or analysis holds up, or answering referee comments on one.

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。

OCR scanned or image-only corpora with vision-language models in three phases: `evaluate` picks a system by measured CER/WER against stratified human ground truth, `run` builds the production pipeline, and `clean` corrects raw OCR with LLM and rule-based passes, diagnostics, and span-level provenance. Born-digital documents with a text layer go to $doc-to-markdown.

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。

Turns a raw Qualtrics conjoint export into an analysis-ready long-format dataset, covering export settings, identifying the implementation, package or manual wide-to-long reshaping, choice-profile alignment, ratings, reference categories, pilot exclusion, and subgroup merges. Use when the user has a conjoint CSV to clean, reshape, or debug, cannot align choices with profiles, or asks what the data must look like before AMCE estimation. Design goes to conjoint-design, validity review to conjoint-diagnostics.

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。

Designs conjoint and factorial-vignette experiments, covering attribute architecture and randomization restrictions, effective-N power, treatment realism, the choice among AMCE, marginal-mean, and AMIE estimands, forced-choice versus rating designs, and PAP tiers. Use when the user is planning a conjoint, drafting or critiquing an attribute table, asking how many respondents or tasks are needed, whether to report AMCEs or marginal means, or how to test interactions. Reviewing an existing design goes to conjoint-diagnostics, cleaning the export to conjoint-cleaning.

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。

Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design integrity, estimation, measurement error, external validity, and interpretation, including the guardrail against reading an AMCE as majority preference. Use when the user asks whether a conjoint design or analysis holds up, has referee comments on a conjoint, or wants a second opinion on estimation or interpretation. New designs go to conjoint-design, reshaping to conjoint-cleaning.

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。

Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"

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Guide a PACK-X author through the SPF fill cycle 01-11. Calls R28 Diagnostician to select mode (assembly/hybrid/full SPF) and leads through phases. Protects the read-only upstream invariant via PreToolUse hook.

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。

Super-skill for developing Haskell projects with cabal nix-style builds. Orchestrates HLS diagnostics, Haddock, Hoogle, source formatting, and cabal-gild into one workflow. Use when writing, editing, refactoring, building, typechecking, fixing compiler errors, renaming symbols, looking up APIs, or changing dependencies in Haskell projects. Treat cabal.project as the source of truth, prefer HLS before full builds, and prefer local docs over remote lookup.

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。

Detect, triage, de-duplicate, and raise compiler bug reports when an agent encounters a likely compiler defect during implementation, review, testing, or issue work. Use when a task surfaces an ICE, panic, wrong accept/reject behavior, miscompile, lowering/emission bug, diagnostic bug, formatter/LSP/frontend drift, or other likely compiler/tooling defect; pause current work, minimize the repro, decide whether the bug blocks the task or has a valid workaround, check whether it is already reported, and then use create-github-issue to raise the bug.

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。

Require corresponding tests for every Go code change, E2E coverage whenever developing tests, and immediate diagnostic remediation while agents edit code; select, run, and maintain AuthCrunch tests through pinned tested, browser tests, automation fixtures, coverage artifacts, and CI gates.

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Audit AuthCrunch security boundaries, triage vulnerability reports and scanner findings, reproduce authentication or authorization failures, and prepare evidence-backed remediation. Covers trust, credentials, redirects, concurrency, diagnostic logging, and dependency exposure.

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。

Audit or design generative AI interfaces against three diagnostic pillars (deterministic-stochastic balance, interaction density, visual cohesion). Treats taste as a measurable control system, not subjective preference. Use when: 'taste audit', 'score this UI', 'design quality', 'interaction density', 'visual cohesion', 'refiner layer', 'correction cost', 'why does this feel off', 'polish this', 'design review', or building any user-facing AI 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。

Use when starting a session and suspecting configuration issues, after hook failures, MCP connection errors, or degraded vault performance. Also useful as a periodic health audit.

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。

Diagnoses firing AWS CloudWatch alarms by querying CloudWatch Metrics, alarm history, and related AWS Config resource snapshots via the AWS SDK. Correlates metric anomalies with recent infrastructure changes to suggest root cause hypotheses. Outputs a structured incident summary with remediation options.

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。

Executes structured diagnostic runbooks when CloudWatch Anomaly Detection triggers alarms. Uses the AWS SDK CloudWatch client (GetMetricData, DescribeAlarms) to gather context and suggest remediations.

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。

Executes automated diagnostics using the AWS Systems Manager Automation API and SSM Documents. Collects system metrics via the CloudWatch GetMetricData API and correlates with AWS Health events.

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。

Diagnoses failed AWS CloudFormation stack operations using the AWS CLI (aws cloudformation describe-stack-events) and cfn-lint validator. Traces resource creation failures, rollback causes, and nested stack dependency chains.

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。

Automates incident response for AWS CloudWatch alarms using boto3, the CloudWatch GetMetricData API, and AWS Systems Manager runbook documents. Maps alarm states to diagnostic procedures and remediation actions.

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。

Executes Ansible playbooks for server diagnostics and remediation using ansible-runner Python SDK. Supports inventory parsing, vault-encrypted credentials, and real-time task output streaming.

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。

Systematic debugging methods, log analysis, and performance diagnostics. Use when debugging issues, analyzing errors, or troubleshooting incidents.

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。