Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
48,168 skills from 2,325 repositories · updated 9 hours ago
48,168 skills
- kiro-spec-batchgotalab/cc-sddCreate complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.PlanningNo warnings★ 3.7K↓ —
- kiro-discoverygotalab/cc-sddEntry point for new work. Determines the best action path or work decomposition (update existing spec, create new spec, mixed decomposition, or no spec needed) and refines ideas through structured dialogue.PlanningNo warnings★ 3.7K↓ —
- session-investigatorevalstate/fast-agentInvestigate fast-agent session and history files to diagnose issues. Use when a session ended unexpectedly, when debugging tool loops, when correlating sub-agent traces with main sessions, or when analyzing conversation flow and timing. Covers session.json metadata, history JSON format, message structure, tool call/result correlation, and common failure patterns.FinanceNo warnings★ 4K↓ —
- posthog-automationdavepoon/buildwithclaudeAutomate PostHog tasks via Rube MCP (Composio): events, feature flags, projects, user profiles, annotations. Always search tools first for current schemas.ProductivityNo warnings★ 3.7K↓ —
- tao-train-mask-auto-labelNVIDIA/skillsMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".OtherNo warnings★ 3.8K↓ —
- nemotron-retrieval-recipesNVIDIA/skillsUse when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.DevOpsNo warnings★ 3.8K↓ —
- nvmolkit-usageNVIDIA/skillsUse when writing or debugging nvMolKit Python code for GPU-accelerated RDKit fingerprints, similarity, conformers, clustering, and molecular searches.WritingNo warnings★ 3.8K↓ —
- kiro-validate-gapgotalab/cc-sddAnalyze implementation gap between requirements and existing codebasePlanningNo warnings★ 3.7K↓ —
- kiro-spec-designgotalab/cc-sddCreate comprehensive technical design for a specificationDesignNo warnings★ 3.7K↓ —
- kiro-spec-tasksgotalab/cc-sddGenerate implementation tasks for a specificationPlanningNo warnings★ 3.7K↓ —Also in 4 other repos
- kiro-spec-statusgotalab/cc-sddShow specification status and progressPlanningNo warnings★ 3.7K↓ —Also in 7 other repos
- kiro-spec-batchgotalab/cc-sddCreate complete specs for roadmap features by dependency wave using Devin subagents when available, with permission-aware sequential and inline fallbacks.PlanningNo warnings★ 3.7K↓ —
- jetson-customize-cameraNVIDIA/skillsEnable MIPI/GMSL camera sensors on a Jetson Thor or Orin custom carrier by rendering a kernel-DT overlay from the in-tree sensor DTSI. Do NOT use for UPHY lane allocation or ODMDATA edits.MediaNo warnings★ 3.8K↓ —
- kiro-spec-initgotalab/cc-sddInitialize a new specification with detailed project descriptionPlanningNo warnings★ 3.7K↓ —
- tao-finetune-cosmos-embedNVIDIA/skillsCosmos-Embed1 video-text embedding for text-to-video retrieval, video-to-video search, semantic deduplication, and fine-tuning. Use when the user asks to "fine-tune Cosmos-Embed1", "run cosmos-embed inference", "export Cosmos-Embed1", "embed videos", or "search videos with text".MediaNo warnings★ 3.8K↓ —
- tao-finetune-kumo-anomalyNVIDIA/skillsKumo-Anomaly — diffusion-based anomaly detection and fine-tuning for multivariate time series. Use when the user asks to "fine-tune Kumo-Anomaly", "run Kumo-Anomaly inference", "detect anomalies with diffusion", "time series anomaly detection", "finetune Kumo-Anomaly", "use perform_anomaly_analysis_with_diffusion", "automl Kumo-Anomaly", "hyperparameter search Kumo-Anomaly", "hyperparameter optimization" or mentions "curriculum_medium.yaml", "final_model.pth", "kumo-anomaly", "sdk/anomaly_analysis", or "TSDiffuser_Generic".OtherNo warnings★ 3.8K↓ —
- kiro-steeringgotalab/cc-sddManage {{KIRO_DIR}}/steering/ as persistent project knowledgeOtherNo warnings★ 3.7K↓ —Also in 5 other repos
- tao-run-inference-serviceNVIDIA/skillsStart, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.DevOpsNo warnings★ 3.8K↓ —
- paid-ads-chatgptnowork-studio/notfair-pluginPlan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. Use for ChatGPT advertising, OpenAI ads, conversational ad concepts, ChatGPT campaign plans, or performance reviews from a verified export.MarketingNo warnings★ 4.1K↓ —
- kiro-steeringgotalab/cc-sddManage {{KIRO_DIR}}/steering/ as persistent project knowledgeOtherNo warnings★ 3.7K↓ —
- competitor-pagesnowork-studio/notfair-pluginCompetitor page gap analysis — take a query you want to win and the pages currently outranking you, and produce a concrete brief on what to add or change to compete. Compares content depth and coverage (subtopics they cover that you don't), structure (headings, format, tables, media), search-intent match, E-E-A-T signals, schema/rich-result eligibility, internal linking, and on-page optimization — across your page vs. the top-ranking competitors. Use this skill whenever the user wants to know why a competitor outranks them on a specific query, what a top-ranking page does better, a content-gap analysis against specific competitor URLs, or a brief to beat a specific SERP. Trigger on: "why does competitor X outrank me", "content gap analysis", "competitor page analysis", "what does the top result have that I don't", "how do I beat this page", "analyze competitor pages", "SERP gap", "compete for [keyword]". For seed keyword discovery use /keyword-research; for a content calendar use /content-planner.ScienceNo warnings★ 4.1K↓ —
- codonfm-setupNVIDIA/skillsSet up the public CodonFM v1 repository and download public Encodon checkpoints. Use for requests to build or launch the CodonFM development container, configure local data/checkpoint mounts, verify GPU access, or download public Encodon 80M, 600M, 1B, or Cdwt-1B weights. Do not use for Decodon, Encodon 5B/10B, missense-aggregation, or codon-optimization setup because those implementations are not in the public repository.OtherNo warnings★ 3.8K↓ —
- content-plannernowork-studio/notfair-pluginGSC-driven content calendar. Pulls real Search Console data, finds the highest click-potential opportunities (striking-distance queries at positions 5-20, unanswered query intent, related-keyword expansions), and produces a dated, prioritized content calendar — ready to hand to /content-writer. Use when the user asks "plan my content", "what should I write next", "content calendar", "content plan", "content roadmap", "editorial calendar", "what topics will rank", "find quick-win SEO topics", "click-potential analysis", or "schedule my SEO content".PlanningNo warnings★ 4.1K↓ —
- tao-train-grounding-dinoNVIDIA/skillsGrounding DINO for open-set object detection. Combines DINO-style detection with a BERT text encoder for language-guided detection — detects objects described by text prompts without a fixed class vocabulary. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Grounding DINO model. Trigger phrases include "train Grounding DINO", "open-vocabulary detection", "text-prompted detector", "language-guided object detection".OtherNo warnings★ 3.8K↓ —
terraform-test
hashicorp/agent-skills
OfficialTestingUpdated 3 days ago
From the author
Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.
Install
npx skills add hashicorp/agent-skills --skill terraform-test -a claude-code
Installs to .claude/skills/terraform-test/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (MPL-2.0) does not let us redistribute its files. The install commands fetch them from GitHub instead.
What it can touch
Instructions onlyNo network use seenLicence: MPL-2.0
Safety checks on SKILL.md
No warnings.
Why 90
Security100
Provenance100
Maintenance100
Licence80
Adoption48
Files (4)
- SKILL.md
- references/CI_CD.md
- references/EXAMPLES.md
- references/MOCK_PROVIDERS.md