Results for “imported”

Import SaaS data into DuckDB using dlt, a data loading tool, then generate a Wren project with table definitions and relationships. Verify the setup with real SQL queries, or start from an existing DuckDB file.

• Importing HubSpot or Stripe data for SQL analysis
• Creating a Wren project from an existing dlt DuckDB file
• Generating table definitions and parent-child relationships

Creates and edits Lark presentations, from planning pages with images and charts to updating specific text or pictures. It also reads existing slides, adds or deletes pages, edits imported PPTX templates, and captures page screenshots.

• Creating a presentation with images and charts
• Updating a title or image on an existing slide
• Adding or deleting presentation pages

Import FBX 3D models into CARLA on UE 5.8 and register them as props that can be placed in a simulation. Check measured dimensions, adjust scale, verify placement on a running server, and undo imports when needed.

• Add a custom bench or object to CARLA
• Fix imported props missing from the blueprint library
• Import a folder of props organized by tag

Import FBX 3D models into CARLA as props that can be placed through its Python API. Handles category tags, measured dimensions, asset registration, and spawn checks for individual files or folders of models.

• Add custom benches and signs to CARLA
• Import a folder of models grouped by tag
• Check model dimensions and spawning

Import an FBX character into a CARLA source build as a pedestrian available through the Python API. Check its GEN3 skeleton, create assets and a walker blueprint, register it, and verify spawning, ground placement, and movement.

• Add a custom FBX character as a CARLA pedestrian
• Check whether an FBX uses the required GEN3 skeleton
• Investigate floating or motionless imported pedestrians

Import a four-wheel FBX vehicle into a CARLA source build, configure its physics, wheels, and animation, and register it for the Python API. Verify that the resulting vehicle can spawn, drive, and steer.

• Importing a custom van or truck into CARLA
• Registering a vehicle for spawning through the Python API
• Checking why an imported vehicle will not drive or steer

Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.

• Assess findings from a vulnerability scanner
• Review security tickets from Jira or Linear
• Evaluate GitHub alerts and security advisories

Audit Microsoft Advertising tracking, search and audience campaigns, Google Ads imports, keywords, bidding, and budgets. Get prioritized recommendations with supporting evidence and clearly marked gaps, while keeping campaign changes outside the audit.

• Check UET tracking and conversion settings
• Review campaigns imported from Google Ads
• Audit keywords, bidding, and budget allocation

Convert an existing frontend into a Stitch design by extracting a standalone HTML file and shared design rules, then uploading both to a project so you can revise the interface in Stitch.

• Move an existing web app into Stitch
• Review React or Vue component designs in Stitch
• Extract design rules alongside screen HTML

Turn an unfinished or completed novel into an organized writing project. The skill analyzes existing text, rebuilds settings and outlines, and prepares the appropriate long or short fiction structure for continued writing.

• Organizing an unfinished novel for continued writing
• Rebuilding settings and outlines from existing chapters
• Preparing an imported novel for the next chapter

Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.

• Assess findings from a vulnerability scanner
• Review security tickets from Jira or Linear
• Evaluate GitHub alerts and security advisories

Turn a demonstrated computer workflow or an imported Chrome Recorder flow into a portable Skill draft. Recordings are named and saved automatically, and users can review or edit steps before exporting the package.

• Creating a Skill draft from a demonstrated workflow
• Importing a Chrome Recorder flow
• Reviewing and editing recorded steps

Generate towers, castles, pagodas, and domes in Three.js from adjustable parameters. Create construction animations with a rising reveal, matching solid sections, scaffolding, and stage captions, using reusable geometry instead of imported mesh files.

• Animate the construction of a castle or pagoda
• Create an architectural title sequence
• Generate landmarks from adjustable parameters

Build and check monsters for Three.js and web action games using shared rules for joints, attachment points, collision shapes, and combat states. Separate visual animation from damage decisions, and provide reproducible checks for attacks and detail-level changes.

• Standardizing joints and attachment points across monsters
• Connecting attack timing with collision and damage handling
• Reproducing combat states and attack phase boundaries

The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve/mute/dismiss issues (alerts, reports, and audit findings) with notes; run and triage audits; see who has access and change roles (e.g. read-only); create or scope API keys (e.g. a push-only CI key); change settings; run saved or ad-hoc ClickHouse queries. Served by the `fp` CLI against FailproofAI Cloud. NOT for writing or designing an evaluator service / scoring logic (that's `agenteye-evaluator`), adding SDK/instrumentation to your app (that's `failproofai-sdk`, imported as `failproofai_sdk`), debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-FailproofAI Cloud secrets).

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Use this skill when NeMo Relay is installed or imported but application-side runtime behavior is missing or incorrect, including load failures, inactive scopes, missing events, and plugin or adaptive wiring problems.

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Cut an imported livestream recording of any genre into evidence-backed, platform-ready clips by combining transcript, visual, audio, interaction, and domain-specific signals. Use for commerce, gaming, talk, interview, education, entertainment, sports, music, IRL, creative, news, or mixed livestream recordings.

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Import Gerber, ODB++, Allegro .brd, .mcm files for PCB boards and IC packages. Inspect nets, layers, shapes, and stackups. TRIGGER: user asks to import, read, or open a PCB layout file. Gerber files use gerberRead or PCBReader; ODB++, Allegro .brd, .mcm, and native formats use pcbFileRead. Also when inspecting nets, layers, components, or stackups from an imported board. Invoke BEFORE writing import code — the query API (cadnet, cadnetList, componentList) is specialized. SKIP: EM analysis or S-parameter extraction (use matlab-analyze-em), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn), building custom geometry (use matlab-assemble-pcb-layout), material/stackup definition only (use matlab-manage-pcb-material).

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PDN DC voltage/current analysis, IR drop, design rule checking, and multi-net batch analysis on imported PCB layouts. TRIGGER: user asks about power integrity, PDN analysis, IR drop, voltage distribution, current density, power nets, or design rule checking on a PCB. Invoke BEFORE writing code — the PDN API chain is specialized and non-obvious. SKIP: importing a PCB file (use matlab-read-pcb-layout), EM field/S-parameter extraction (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), transmission line design (use matlab-design-pcb-transmission-line).

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Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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Audit the vault for material that should not be in it: credentials, other people's private information, confidential work, and anything the user would not want synced or backed up. Use this skill when the user asks about privacy, is about to share or sync the vault, has just imported chat history or meeting notes, or asks what is sensitive in their notes. Do NOT use to delete anything on your own, or as a substitute for the publishing check.

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Configure and troubleshoot CCAM Remote Data Sources that collect Claude Code and Codex history over SSH. Use when adding, editing, testing, syncing, or removing a remote machine, verifying provider paths, or deciding whether to retain or purge imported sessions.

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HiContacts provides a collection of tools to analyse and visualize Hi-C datasets imported in R by HiCExperiment.

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Analyze CVE reachability in software repositories by examining how vulnerable dependencies are imported and used. Determines whether vulnerable components, classes, or functions are reachable from project code through call chain analysis, reflection detection, dynamic loading patterns, and configuration-gated behavior. Classifies each CVE as likely reachable, possibly reachable, or likely unreachable with supporting evidence. Use when analyzing security vulnerabilities in dependencies, performing post-disclosure CVE triage, assessing vulnerability impact, or when users ask to analyze CVE reachability, check if vulnerabilities are exploitable, or evaluate dependency security risks.

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