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Found 350 Skills
Integrates OpenTelemetry tracing, metrics, and logging into iii workers. Use when setting up distributed tracing, Prometheus metrics, custom spans, or connecting to observability backends.
Create, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
AI project intelligence system. Manages .ai/ directory for rules, behaviours, sessions, incidents, memory, snapshots, and learning loops. Use when: starting a session, switching behaviour, logging an incident, saving feedback, reviewing past sessions, checking active hotfixes, managing snapshots, creating snippets/prompts. Proactively suggest when: user corrects AI behavior ("no", "don't", "wrong", "stop", "always", "never"), session ends, a mistake pattern repeats, starting work on unfamiliar code, user says "remember this" or "learn this".
Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /cs:decisions, or checking overdue action items with /cs:review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.
Build immutable audit trails for all financial transactions with user attribution, change logging, tamper detection, and compliance-ready export for external audits
Guides privacy research engineering for safeguards—PII and sensitive-data detection research, redaction and de-identification evals, memorization and extraction risk studies, privacy benchmarks and labeled corpora, logging/retention minimization for safety pipelines, and research memos on privacy–utility trade-offs for guardrail systems. Use when measuring PII detector quality, designing privacy eval suites for moderation stacks, studying training-data leakage or prompt logging risk, or recommending privacy mitigations for safeguard models—not for SOC 2/GDPR evidence automation (compliance-engineer), legal DPIA or AI policy (ai-risk-governance), harm/toxicity classifier R&D (ml-research-engineer-safeguards), production inference gateways (ml-infrastructure-engineer-safeguards), or general non-privacy research (ai-researcher).
Design structured logging systems with context propagation. Use to ensure Python applications are observable and logs are machine-readable.
Debug logging, Debug menu, runtime pitfalls, typing-latency-sensitive paths, SwiftUI list snapshot boundaries, OS-version repros, and local visual iteration for cmux. Use when adding debug probes, diagnosing UI/runtime issues, touching terminal rendering, tab/sidebar list views, drag/drop UTTypes, or using the Debug menu.
Explains middleware concepts, patterns, and implementations. Covers server middleware, edge middleware, request/response pipelines, and common use cases like auth, logging, and CORS. Use when implementing middleware or understanding request processing pipelines.
Expert guidance for building smart contracts on Stellar using the Soroban Rust SDK. Use this skill when working with Soroban smart contracts for tasks including (1) creating new contracts with [contract] and [contractimpl] attributes, (2) implementing storage with Persistent, Temporary, or Instance storage types, (3) working with auth contexts and authorization, (4) handling tokens and Stellar Asset Contracts, (5) writing tests with testutils, (6) deploying contracts, (7) working with events and logging, (8) using crypto functions, (9) debugging contract errors, (10) security best practices and vulnerability prevention, (11) avoiding common security pitfalls like missing authorization, integer overflow, or reinitialization attacks.
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Server Actions and routes, implementing logging wrappers, adding performance instrumentation, or establishing observability for debugging production issues.
Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification protocols, symptom analysis, regression prevention. Actions: debug, investigate, trace, analyze, validate, verify bugs. Keywords: debugging, root cause, bug fix, stack trace, error investigation, test failure, exception handling, breakpoint, logging, reproduce, isolate, regression, call stack, symptom vs cause, hypothesis testing, validation, verification protocol. Use when: encountering bugs, analyzing test failures, tracing unexpected behavior, investigating performance issues, preventing regressions, validating fixes before completion claims.