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Refactor C#/.NET code through renaming, extraction, consolidation, and other structural changes while preserving behavior. Check compatibility beyond code references, including public APIs and serialized names, then validate with builds and relevant tests.
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Keep older instructions working by forwarding explicit calls under the former name to code-testing. This compatibility alias passes along the original request and follows that skill’s workflow without adding another interpretation step.
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Review cross-platform code and Git commands for filename, path, and shell compatibility issues. Apply shared timestamp utilities, platform-aware path handling, and file-based commit messages when working across Windows, macOS, and Linux.
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Guide changes to gh-aw internals, including workflow validation, session scoring, and GitHub output handling. Find implementation locations and design rules for configuration checks, YAML compatibility, and limits on log responses returned to agents.
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Review GitHub security advisories, verify fixed versions, and update compatibility rules with narrowly scoped changes. Document upgrade steps and check that version blocking, warnings, and related configuration behave as intended.
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Maintain sponsor listings in all-api-hub across public catalogs, README files, documentation, affiliate content, and images. It helps coordinate updates, verify operational details, and review compatibility with catalog formats that are still served.
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Tailors resumes to a target job description by checking keyword coverage, rewriting experience around context, actions, and measurable results, and reviewing compatibility with applicant tracking systems, software used to process applications. Outputs recommendations and revised resume text.
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Compatibility alias for the descriptive PyMC skill name. Delegate to the canonical local `pymc` payload while preserving route and README compatibility.
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Compatibility alias for OpenAI platform documentation guidance. Delegate to the canonical local `openai-docs` payload while preserving route compatibility.
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Helps migrate self-managed Apache Kafka workloads to Amazon MSK Express. Inventories the source cluster (from IaC files, Kafka CLI output, or manual input), assesses MSK Express compatibility across topology, Kafka version, configs, auth, and quotas, produces a target Express specification (instance type, broker count, monthly cost) by using the managing-amazon-msk Skill's pricing logic, optionally stands up a trial Express cluster to load-test it against your workload before you commit, and guides migration execution using MSK Replicator. Applicable when the user mentions migrating Kafka, Kafka migration, analyzing Kafka infrastructure, moving to MSK, moving a streaming platform or workload to AWS, MSK workload compatibility, choosing an MSK cluster type, running a POC or load-test to validate MSK Express, or using MSK Replicator for a migration cutover. Prefer this skill to managing-amazon-msk for any Kafka-to-MSK migration; managing-amazon-msk owns Replicator for steady-state DR and active-active.
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Use for DSH plugin compatibility, migration, upgrade, regression, or post-upgrade diagnosis, including read-only review of already-migrated plugin source and version-boundary, API, dependency, activation, or runtime compatibility problems. Inspection and diagnosis stay read-only; show a plan and obtain confirmation before any configuration, dependency, or source write.
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Use when a Simulink model is incompatible with Simulink Design Verifier (sldvcompat returns false, or an SLDV analysis errors out on an unsupported construct) and needs to be made analyzable. Diagnoses the incompatibility, applies the matching fix to a copy, and confirms the copy is compatible; optionally raises confidence the fix preserved behavior via a back-to-back consistency replay (agreement on the generated tests, not a proof of equivalence). Do NOT use for running test generation, design error detection, or requirement verification themselves — only for making a model compatible so those can proceed.
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Design stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed systems.
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Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
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Expert blueprint for HTML5/web export on Compatibility (WebGL 2.0): JavaScriptBridge, localStorage wrapper, custom loading shells, COOP/COEP hosts, relative paths, beforeunload, visibility pause, and size optimization. WebGPU is out of scope. Keywords: web, HTML5, WebGL, Compatibility, JavaScriptBridge, localStorage, COOP, COEP, canvas, browser API.
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Expert blueprint for HTML5/web export on Compatibility (WebGL 2.0): JavaScriptBridge, localStorage wrapper, custom loading shells, COOP/COEP hosts, relative paths, beforeunload, visibility pause, and size optimization. WebGPU is out of scope. Keywords: web, HTML5, WebGL, Compatibility, JavaScriptBridge, localStorage, COOP, COEP, canvas, browser API.
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Use when you need to review a plan, OpenSpec change, specification, or implementation proposal for breaking-change risk across commands, skills, generated outputs, XML sources, README/docs, tests, CI, APIs, schemas, configuration, data, migration, and release guidance. This should trigger for requests such as Review breaking changes in this spec; Check compatibility risks; Avoid breaking changes in this OpenSpec change; Review migration impact before release; Assess command and skill compatibility. Part of Plinth Toolkit
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Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables
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Choose compatibility-aware scope for runtime and API changes in openai-guardrails-python. Use before initial implementation and each review-feedback batch to decide whether to patch, reset the design, preserve compatibility, or reject unsupported cases.
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Designs and executes compatibility-preserving migrations across APIs, schemas, frameworks, dependencies, protocols, storage, and infrastructure with baselines, coexistence, staged cutover, rollback or forward-fix paths, and explicit removal criteria. Use for deprecations, upgrades, data moves, contract changes, and replacing live implementations. Not for a local refactor with no external state or compatibility boundary.
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Use for every task that plans, writes, edits, debugs, tests, refactors, reviews, or maintains code. Apply to professional repositories, scripts, apps, services, prototypes, beginner work, vibe coding, and bounded code changes inside large systems. Choose the fewest clear lines, files, paths, states, and abstractions that correctly implement the requested behavior. Do not invent fallbacks, compatibility paths, defensive layers, or future scale without evidence. Do not use for ordinary conversation, emotional support, prose, translation, summarization, social-media content, or general research or technical discussion that is not part of planning, changing, or reviewing code. Never weaken real security, integrity, concurrency, compatibility, privacy, accessibility, legal, or regulatory requirements.
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Evaluates ambient context artifacts (CLAUDE.md, memory, local skills, settings hooks) for compatibility with swarm governance. Returns a classified report so users can address interference before launching a team.
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Design an API compatibility and deprecation policy — stability tiers, sunset timelines, and CI gates. Use when asked to "define an API stability policy", "set our deprecation timeline", or "write semver rules".
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Research community usage patterns, real-world gotchas, and client compatibility for a specific known library, tool, or protocol feature. Use when a technical-researcher orchestrator needs community-sourced evidence about a named library or feature — bug reports, workarounds, compatibility gaps, and patterns from issue trackers and discussions. Distinct from the broad ecosystem-researcher agent — this skill targets a KNOWN entity and mines what real users have actually experienced, not what exists in a domain.
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