Agent Skills catalog · page 129
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NVIDIA-TAO/tao-skill-bank
tao-launch-workflow
The mandatory pre-launch gate and four-verb execution contract for every TAO workflow or action. Invoke BEFORE launching anything side-effecting — AutoML, train, evaluate, inference, export, TensorRT engine generation, or DEFT/application workflows — on any execution platform. Covers platform selection, credentials, image confirmation, dataset intake, preflight, the launch review, job records, monitoring, and failure/retry classification. Trigger phrases include "train this model", "run AutoML",
NVIDIA-TAO/tao-skill-bank
tao-run-deft-iaa
Run iterative improvement for NVIDIA TAO CLIP / SigLIP image-text retrieval on attribute-labelled data. Use when a request combines retrieval evaluation, weak-attribute or caption-pair mining, repeated retraining, and a stopping condition based on a retrieval KPI, validation plateau, or iteration budget; the customer need not know the DEFT or Image Attribute Augmentation (IAA) names. The self-contained workflow performs dataset preparation, zero-shot evaluation, attribute gap analysis, caption-s
NVIDIA-TAO/tao-skill-bank
tao-run-deft-object-detection
Run the full DEFT smart-data-augmentation loop for NVIDIA TAO Grounding DINO object detection: zero-shot baseline inference, KPI analysis, per-class gap analysis, SigLIP embedding of weak images, unique-neighbor mining against a source pool, ODVG dataset staging, and retraining — repeated for a fixed number of iterations. Also prepares the source pool the loop mines from, as a separate run: Co-DETR pseudo-labeling, folding to the target classes, KITTI→COCO→ODVG conversion, and embedding. Use for
NVIDIA-TAO/tao-skill-bank
tao-train-grounding-dino
Grounding 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".
NVIDIA-TAO/tao-skill-bank
tao-train-oneformer
OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".
NVIDIA-TAO/tao-skill-bank
tao-train-rtdetr
RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and quantization for deployment optimization. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO RT-DETR model. Trigger phrases include "train RT-DETR", "real-time DETR", "low-latency object detection", "RT-DETR distillation / quantization".
zby/commonplace
analyse-agentic-system
Use when asked to analyse, review, or refresh an external agentic system — an agent runtime, harness, orchestration framework, or agent operating layer, or any narrower system whose deployed behavior depends on model calls plus surrounding machinery.
zby/commonplace
cp-skill-revise-autoreason
Experimentally revise a note with fresh critic, author, synthesizer, and blind-judge agents while retaining the incumbent as fallback.
zby/commonplace
cp-skill-write
Write one KB note whose intended contribution is already determined, under its collection and type contracts; validate it and hand broader graph discovery to cp-skill-connect.
zby/commonplace
cp-skill-write-multistage
Write or rebuild a KB artifact through reconstruction, claim disposition, drafting, audit, and promotion. Use when claims need grounding, synthesis, or separation across multiple artifacts; avoid it for settled local edits.
paleo/alignfirst
top-down-typescript
TypeScript and JavaScript coding style conventions, centered on top-down narrative ordering (caller first, helpers below) and functions over classes. Read before writing or reviewing TypeScript/JavaScript code, including code inside a spec or a plan.
zby/commonplace
write-agent-memory-system-review
Write or update a local code-grounded agent memory system review from a GitHub repository reference, including checkout refresh, optional sub-agent drafting, semantic QA, and validation.
runxhq/runx
ops-desk
Operate a project, workspace, or account from an agent or manager dashboard: inspect state, triage risks, prepare governed actions, route to the right skill lane, require approvals for consequential acts, and verify receipts after execution.
runxhq/runx
data-store
Govern provider-agnostic data reads and state transitions through declared data-source operations, not model-authored raw queries.
runxhq/runx
sourcey
Generate documentation for a project using Sourcey.
runxhq/runx
skill-lab
Canonical Runx skill-authoring implementation. Use for designing, creating, updating, improving, or adding harness coverage to a Runx skill package; it combines bounded agent judgment with native file writes, inspection, and safe harness validation. When a host skill-creator also triggers, use its general guidance but execute Runx work through this skill.
avivsinai/agent-message-queue
amq-cli
Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need t
nelsonwerd/idea-to-ship-skills
deep-dive
Rigorous multi-agent deep-dive analysis for complex investigative tasks — auditing codebases, evaluating strategies or systems, validating designs, doing open-ended research. Deploys 4–6 specialist agents in parallel across distinct lanes, then synthesis, then adversarial red-team review, then optional patching — producing structured markdown research files plus a plain-English executive briefing with honest 1–10 confidence ratings. ALWAYS invoke when the user says any of "deep dive", "thorough
meshy-dev/meshy-3d-agent
meshy-3d-generation
Generate 3D models, textures, images, rig characters, and animate them using the Meshy AI API. Handles API key detection, setup, and all generation workflows via direct HTTP calls. Use when the user asks to create 3D models, convert text/images to 3D, texture models, rig or animate characters, or interact with the Meshy API. For 3D printing requests, use the meshy-3d-printing skill instead.
neondatabase/agent-skills
neon-postgres-branches
Choose and create the right Neon branch type for testing and development. Use when users ask about Neon branching, migration testing with real data, isolated test environments, schema-only branch workflows for sensitive data, resetting a branch from its parent, branch expiration and CI/CD branch lifecycles, or branch creation via Neon CLI or Neon MCP. Triggers include "Neon branch", "test migrations safely", "branch production data", "schema-only branch", "reset branch", "branch per PR" and "sen
nelsonwerd/idea-to-ship-skills
autopilot
Run the idea-to-ship pipeline AUTONOMOUSLY, in character as a grounded founder-persona — composing ideate → deep-dive → prompt-pack → build-loop to take a real, grounded niche to a near-finish-line-AIMED first-draft product plus an honest ledger of what only a human or the market can finish. ALWAYS invoke when the user says any of "run autopilot", "build this idea→ship autonomously", "spin up a grounded founder and build it", "fly the whole pipeline end to end", or "autonomous first-draft from a
neondatabase/agent-skills
neon-functions
Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASE_URL injected automatically and compute that runs next to your data. Use when a user wants to host an API, an AI agent with long streaming responses, a WebSocket or server-sent-events (SSE) server, a webhook handler, a Discord bot, an MCP server, or any request/response workload that risks timing out on short, lambda-style serverless functions — and wants it to branch with their database. Triggers includ
vasilyu1983/AI-Agents-public
agents-hooks
Configures Claude Code hooks and Codex hooks.json/notify callbacks. Use when adding guardrails, preflight, audit trails, worktree automation, or budget enforcement.
vasilyu1983/AI-Agents-public
qa-testing-ios
Guides iOS testing with XCTest, XCUITest, Swift Testing, simctl, and xcresult. Use when choosing destinations, controlling flakes, or parsing test artifacts for native apps.