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Analyze production Agentforce agent behavior using session traces and Data Cloud, and manage Agent Health Monitoring (AHM) alerts. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries; creates, lists, updates, or deletes an AHM data alert on an agent metric (escalation rate, deflection, etc.); asks why an alert is not firing or wants to check whether alerts have fired (notification counts, or the per-alert Incidents view). DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use agentforce-generate); writes or runs test specs (use agentforce-test); uses sf agent preview for local development iteration; deploys or publishes agents.

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Use when the user asks for Superloopy clone or asks to clone, rebuild, reverse-engineer, replicate, or copy a website or page into a Superloopy-governed implementation. Triggers on "loopy clone", target URLs plus requests such as "clone this site", "rebuild this page", "make a copy of this website", "pixel-perfect clone", or "AI website clone". Requires browser automation and records component specs, assets, implementation, build output, and visual QA as Superloopy evidence.

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Bug-fix routine that fixes the whole class of bug, not just the reported instance. Use for any bug report, failing production behaviour, monitoring alert, audit finding or review finding that does real harm (a smaller review finding goes on the item's list, as ship-check says), and whenever the same kind of bug has been seen before. Reproduces it with a failing test, names the failure class, searches the task's scope for the same pattern (the whole codebase when the user's own prompt asks for the fix, not when it is picked from a task's list), fixes or records every hit, and adds the rule, invariant, helper or check that stops it coming back.

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Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

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Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.

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Writes or updates engineering documentation and architecture decision records from repository facts, explicit assumptions, trade-offs, and verification links. Use for README changes, design docs, runbooks, ADRs, migration notes, and contributor documentation. Not for implementation planning alone or for copying external documentation without provenance.

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Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.

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Set up, adopt, refresh, or audit a repository's agent instructions (the AGENTS.md block) so AI agents work well in that repo. Also records observed agent mistakes as pitfalls. Use when invoked by name

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Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

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Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.

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Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.

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Verify mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local success into device, cloud, release, or formal acceptance claims.

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Use whenever the user mentions Zenodo, depositing or publishing research artifacts (datasets, software, papers, posters) to Zenodo, minting a DOI for a dataset/code release, uploading files to a Zenodo record, creating a new version of a Zenodo deposit, or searching Zenodo records. Covers the full Zenodo REST API workflow — create deposition, upload files via the bucket API, set metadata, publish, version, and search — for both production (zenodo.org) and sandbox (sandbox.zenodo.org).

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Craft CMS 5 PHP coding standards and conventions. ALWAYS load when writing, editing, reviewing, or discussing any PHP in a Craft plugin or module — even small edits. Also when running ECS, PHPStan, or scaffolding with ddev craft make. Covers: PHPDoc blocks (@author, @since, @throws chains), section headers (=========), class organization, naming conventions (services, queue jobs, records, events, enums), defineRules() and validation, beforePrepare() and addSelect(), MemoizableArray, DateTimeHelper vs Carbon, strict_types/declare(strict_types=1), short nullable notation (?string), typed properties, void returns, control flow (early returns, match over switch), CP Twig template conventions, form macros, translations (Craft::t), ECS/PHPStan config, scaffolding commands, and the verification checklist.

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Craft CMS 5 plugin and module development — extending Craft with PHP. Covers elements, element queries, services, models, records, controllers, migrations, queue jobs, console commands, field types, native fields, events, behaviors, Twig extensions, widgets, filesystems, permissions, project config, GraphQL, testing, and debugging.

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HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data 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。

HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data 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。

HealthSim generates realistic synthetic healthcare data for testing EMR systems, claims processing, pharmacy benefits, and analytics. Use for ANY request involving: (1) synthetic patients, clinical data, or medical records, (2) healthcare claims, billing, or adjudication, (3) pharmacy prescriptions, formularies, or drug utilization, (4) HL7v2, FHIR, X12, or NCPDP formatted output, (5) healthcare testing scenarios or sample data generation.

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Automatically detect and de-identify PII (Personal Identifiable Information) and PHI (Protected Health Information) from clinical/medical text to ensure HIPAA compliance. Trigger when processing medical records, patient data, clinical notes, insurance information, or any healthcare-related text containing potential patient identifiers.

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Personal assistant for the [YOUR LAST NAME] family. Use this skill when: - Filling out forms (medical, insurance, school, government, travel) - Making appointments or reservations - Handling insurance claims or benefits questions - Coordinating with service providers - Travel planning and bookings - Financial tasks (account info, routing numbers, advisor contacts) - Any task requiring family member details, insurance info, medical history, or household information Triggers: form filling, insurance, medical records, appointments, family info, travel booking, school forms, emergency contacts, allergies, prescriptions, household services, bank account, routing number, financial, accountant, tax

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Review a draft contract for scope, term, payment, indemnity, insurance, records, termination, and operational red flags.

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Personal document management skill using Paperless-ngx. Use when: (1) Ingesting and filing new documents, (2) Searching for existing documents, (3) Applying tags and correspondents, (4) Managing retention policies, (5) Integrating documents with other personal workflows (tax prep, medical records, insurance claims). Tools: paperless-mcp for all document operations.

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Coterie Insurance integration. Manage data, records, and automate workflows. Use when the user wants to interact with Coterie Insurance data.

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Query Lore, the librarian agent, to search the owner's personal knowledge base. Use when looking up stored documents, personal records, insurance, manuals, notes, vehicles, or any "do I have a document about X?" type question.

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。