Results for “skill-files”

Package skills into publishable plugin or bundle formats across ClawHub, Claude, Hermes, AgentSkill, AgentSkills.so, and GitHub. Use when: converting a skill into a release plugin, generating manifests, trimming runtime-only files, and assembling a breakout-ready upload artifact.

Verifies data structures, files, YAML blocks, or agent output against their defined schema, producing a pass/fail report with actionable fix instructions.

Analyzes test coverage reports, identifies under-covered files, and generates missing tests to reach 80% or higher coverage.

Migrate test files from `as` type assertions to @total-typescript/shoehorn, using fromPartial and fromAny for partial or intentionally wrong test data.

Interactive installer for Everything Claude Code — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.

Interactive installer for Everything Claude Code — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and...

Read and write genomic alignment and variant files in Python with pysam (htslib bindings) — SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, plus region extraction and per-base coverage/pileup. Use when scripting NGS data-processing pipelines that parse, filter, index, or compute coverage over BAM/CRAM/VCF files. Part of the AlterLab Academic Skills suite.

Guides users through installing Everything Claude Code skills and rules to user-level or project-level directories, verifying paths and optionally optimizing installed files.

Ingest, index, search, edit, and generate video and audio assets from files, URLs, RTSP feeds, or desktop capture, with real-time alerts and stream links.

Scans root uv.lock and package-lock.json files with the pinned osv-scanner CLI and emits deterministic advisory records. Opt-in: copy this directory into <home>/skills/dependency-advisory-watch/ and install osv-scanner.

Generate videos or music as asynchronous media artifacts. Use this skill when the user asks for text-to-video, image-to-video, first-and-last-frame video, multi-reference-image video, music, a song, a soundtrack, or background music. This skill creates video/music files; it is not for text-to-speech.

Validates agent configuration files for Skills, Hooks, MCP, Memory, and Plugins across Claude Code, Cursor, GitHub Copilot, and Codex CLI against 230 rules, with optional auto-fixing.

>- Skill Refiner, the eval-guided improvement loop for SKILL.md files. Runs the bootstrap, score, propose, apply, and status cycle as a thin wrapper over the published @intentsolutions/refiner CLI, proposing safe, minimal, bounded SKILL.md edits and accepting an edit only when a held-out eval score strictly improves with no regression on any other case. Ships a 3-layer cost-tiered hook architecture (sinker, line, hook) that gates skill quality at edit time, end of turn, and commit time. Use when improving an existing skill, refining a SKILL.md against measured behavior, bootstrapping an eval set for a skill, or gating skill edits before they ship. Trigger with "/j-rig", "refine this skill", "bootstrap an eval set", "propose a skill edit", "promote the candidate", or "skill refiner status".

Optional low-priority poller that inventories Worklink tool pins from <home>/worklink.yaml and files/reuses Chainlink bump issues when upstream versions drift. Opt-in: copy this directory into <home>/skills/worklink-tool-pins/ and configure tool_pins in worklink.yaml.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Provides file paths to language-specific reference files for polyglot test analysis skills, enabling framework-aware detection of test markers, assertions, and patterns across .NET, Python, TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++.

Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Use this skill when the user asks about CMV maintenance program requirements under 49 CFR 396.3 — what records must be kept, retention periods (12-18 months on vehicle file + 1 year after disposal), what counts as systematic inspection/repair/maintenance, preventive maintenance scheduling, brake adjustment records, and what auditors look for in vehicle files. Cite 49 CFR 396.3 + 396.21.

Use when creating new Excalidraw diagrams or reading, modifying, or comparing existing .excalidraw or .excalidraw.json files. Also use when the user asks for hand-drawn style diagrams, whiteboard sketches, architecture diagrams in Excalidraw format, or wants to export Excalidraw to SVG/PNG. Use this skill even if the user doesn't say "Excalidraw" — for example when they ask for a system diagram, flowchart, or architecture sketch that should look hand-drawn or informal.

Sharpens and stress-tests an existing plan file through multiple codebase-grounded review passes, editing it in place and recording every finding and iteration in cross-referenced companion files. Use this skill whenever the user wants to iterate on, refine, tighten, or improve a plan. Also use it when the user asks to verify, validate, or confirm feasibility of an approach. Does not implement plan steps, write test plans, review code, or investigate bugs, and does not generate new plans from scratch — use plan-a-feature for a new plan. Runs its review rounds to completion without pausing between them; to review each round as it lands, use pairing.