「responses」の検索結果

Script a multi-turn tutoring dialogue with branching responses for anticipated student difficulties. Use when designing AI tutors, chatbot interactions, or structured one-to-one support scripts.

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。

Evaluate a teacher-drafted central historical question for its capacity to drive genuine historical inquiry. Use when assessing whether a question will generate real evidence-weighing or produce shallow responses.

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。

Design a multi-round questioning sequence for interrogating AI chatbot answers, tracking how responses shift and distinguishing genuine updates from sycophantic capitulation. Use when teaching students to probe AI critically.

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。

Investigate and resolve Course Management Platform CloudWatch alert issues end to end. Use when Codex is asked to inspect a CMP GitHub alert issue, pull dev or production AWS logs, diagnose 5xx responses or failed background work, fix an incident with test-driven development, validate a fix in dev, or deploy and verify an authorized production fix.

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。

Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatStatus, streamText, toUIMessageStreamResponse, addToolOutput, onToolCall, sendMessage.

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Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.

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Use this skill for insurance-claims operations with Stedi whenever the user asks to submit claims, validate claim payloads, check claim status, retrieve/interpret 277CA or 835 responses, troubleshoot payer/provider enrollment requirements, or build deterministic claims workflows. Trigger this skill even if the user does not say "Stedi" explicitly but mentions 837/835/277CA/ERA, payer IDs, claim rejection codes, claim resubmission, COB, or healthcare clearinghouse automation.

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Amazon Bedrock Automated Reasoning for mathematical verification of AI responses against formal policy rules with up to 99% accuracy. Use when validating healthcare protocols, financial compliance, legal regulations, insurance policies, or any domain requiring deterministic verification of AI-generated content.

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Write support playbook -- response templates, issue-type runbooks, tone guide, and common resolution paths. Use when asked to "write support templates", "build a support playbook", "train our support agents", or "standardize our support responses".

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```yaml name: cognitive-surrogate description: Layer 6 Barton Cognitive Surrogate System - build, train, and validate psychological models that predict and generate authentic responses matching a subject's cognitive patterns version: 1.0.0 trit: 0 # Ergodic/coordinator role in GF(3) triadic system ```

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Intercept and debug Claude Code API requests using mitmproxy. Inspect system prompts, tool definitions, token usage, and streaming responses. Triggers: cc-trace, mitmproxy, API interception, Claude Code debugging, traffic inspection.

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REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.

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Use Verify for snapshot testing in .NET. Approve API surfaces, HTTP responses, rendered emails, and serialized outputs. Detect unintended changes through human-reviewed baseline files.

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Drafts a referee report for a journal editor. Produces a recommendation, claim-and-design summary, three to six decision-driving concerns, additional concerns, and a revision plan through five parallel adversarial finders, Breaker, Butcher, Shredder, Void, Situator, a Blue Team error filter, Chief Reviewer synthesis, Tone Guard legal pass, and optional confidential editor note. Use when the user has been asked to referee a manuscript. Self-audits go to paper-review-lite or presubmit, and author responses go to referee-response.

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Advises on setting up and validating topic models for survey and experimental text. Covers the discovery-versus-measurement question, choosing STM, LDA, or BERTopic, preprocessing consequences, prevalence and content formulas, topic-count selection across coherence, exclusivity and FREX, held-out likelihood, and residuals, validation of topics against human judgment, robustness, and DA-RT-compliant reporting. Use when the user has open-ended responses or another corpus and asks what topics are present, how many topics to use, about STM, searchK, coherence, or FREX, or wants topic prevalence compared across treatment arms or countries. Fixed-codebook coding goes to text-classification.

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Draft a referee report on someone else's manuscript for a journal editor, using five adversarial finders, a Blue Team error filter, a Chief Reviewer synthesis, and a Tone Guard legal pass. Use when the user has been asked to referee a manuscript; self-audits go to paper-review-lite or presubmit, author responses to referee-response.

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Build RAG (Retrieval-Augmented Generation) agents with Google ADK and Vertex AI RAG Engine. Use when implementing document Q&A, knowledge base search, or citation-backed responses. Covers VertexAiRagRetrieval tool, corpus setup, and citation formatting.

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Update the application tracker. Record replies (rejection, screening, interview, offer), log an application the user made by hand, or sweep the inbox for replies. Use when the user runs /seekter-log, says a company replied or rejected them, or asks to check emails for responses.

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Automate on-target verification of a program's logic by driving its RTT console with rttsh - write Lua scripts that exercise commands and assert responses, output and timing on real hardware. Use when asked to verify target-side behavior on board, build board-level checks for firmware features, or automate hardware test runs.

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Maps ACF field groups into predictable REST responses using `acf_add_local_field_group`, `get_field_objects`, and `register_rest_field`. Useful when you need cleaner payloads than the default ACF exposure and want WordPress clients to consume structured field data safely.

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Expert sales proposal and pricing presentation strategist. Use when writing proposals, executive summaries, ROI business cases, pricing presentations, SOWs (Statement of Work), RFP responses, or competitive positioning documents. Covers proposal structure, terms positioning, design formatting, follow-up strategy, and win-rate optimization.

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Use when working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).

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Use ManagedCode.MimeTypes when a .NET application needs consistent MIME type detection, extension mapping, and content-type decisions for uploads, downloads, or HTTP responses.

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Builds corporate scenario planning models with macro assumption sets, strategic response options, and contingency plan development. Use when building scenario frameworks, planning strategic responses, or developing contingency strategies.

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。