Results for “media-merger”

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining, covering SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

Merges mature lessons from a domain memory file into its instruction file, preserving knowledge with minimal redundancy.

Merges agent or review outputs into one deduplicated, evidence-linked, severity-ranked actionable report.

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

Combines multiple pipe-format blocks from conversation context into one unified output, handling deduplication, source attribution, and confidence upgrades.

Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.

Manage document merger operations. Auto-activating skill for Business Automation. Triggers on: document merger, document merger Part of the Business Automation skill category. Use when working with document merger functionality. Trigger with phrases like "document merger", "document merger", "document".

Expert en médias avancé (content strategy, distribution, monetization, AI generation, DZ context)

CapsFusion: Rethinking Image-Text Data at Scale

Merge the winning agent's branch into the base branch, archive losing branches via git tags, and clean up worktrees after an AgentHub competition session.

Merge the winning agent's branch into base, archive losers, and clean up worktrees.

동시에 굴리던 여러 워크트리를 한 번에 통합합니다. 각 워크트리와 연결된 이슈를 확인하고 증거로 실제 해결 여부를 판정한 뒤, merge 를 시도하기 전에 충돌을 확정하고 계획한 순서대로 누적 검증해 순서 때문에 깨지는 경우까지 잡아냅니다. 충돌은 작업 브랜치 쪽에서 양쪽 의도를 보존하는 방향으로 해소해 승인받고, 비판 서브에이전트로 모호성을 걸러낸 다음 PR 을 merge 하고 통합 테스트로 재검증하고 이슈를 닫습니다. `$issue-merge`, "워크트리 전부 merge", "이슈들 통합", "PR 충돌 해결하고 합쳐줘" 요청과 issue-end 에서 merge 를 선택했을 때 사용합니다.

Sync the branch with the latest `origin/main`, merge `origin/main`, resolve conflicts end-to-end, then commit and push the current branch.

Integrate an exact reviewed PR under repository policy, choose truthful history semantics, and verify cleanup

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Use when using RTMS.

Pre-Merge Brief

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.

Merge the winning agent's branch into base, archive losers, and clean up worktrees.

Use when blending editorial magazine composition with precision product-tech detailing — asymmetrical grids, cinematic media bands, mono utility labels, and restrained accent color. Prefer this over mengto-agency-grid-layout-minimal when tech/product detailing and media bands matter as much as the editorial grid.

Composite skill — take a PR from "I think it's ready" to merged with full gate verification. Chains pr-merge-readiness (verdict) → ci-watch / gh-fix-ci (if blockers) → gh-address-comments (if review needed) → ship (when verdict is MERGE). Use as the one-call answer to "can I merge this?" instead of running 4 skills sequentially.

Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.

通过 fal.ai MCP 实现统一的媒体生成——图像、视频和音频。涵盖文本到图像（Nano Banana）、文本/图像到视频（Seedance、Kling、Veo 3）、文本到语音（CSM-1B），以及视频到音频（ThinkSound）。当用户想要使用 AI 生成图像、视频或音频时使用。

Resolves, generates, and operates on media assets (audio, images, icons, logos, voice, color grades, LUTs) for HyperFrames projects, using a local cache and the HeyGen CLI for free-usage catalog search and TTS.

Detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using the Resemble AI platform.

Google and Meta paid media account structure evaluation. Audits campaign/ad set architecture against conversion volume minimums, budget thresholds, and targeting overlap. Identifies over-segmentation, under-segmentation, budget fragmentation, and structural anti-patterns blocking algorithmic learning. Provides consolidation roadmaps with migration plans. Use when inheriting accounts, quarterly health checks, or before scaling budgets.

Generate images and videos with AIsa. Supports Gemini, Wan, and Seedream image generation plus Wan text-to-video and image-to-video models. One API key; the bundled client routes each model to the correct endpoint automatically. Use when: you need a neutral AIsa media-generation skill that spans multiple model families without changing credentials or request flow.

Generates images, videos, and audio using fal.ai models via MCP, covering text-to-image, text/image-to-video, text-to-speech, and video-to-audio.

Combine a human selfie and product image into a UGC-style video ad with a generated script and animated video.

Generates images, videos, and audio using fal.ai models via MCP, covering text-to-image, text/image-to-video, text-to-speech, and video-to-audio.

Use when merging a single GitHub pull request. Handles pre-flight checks, waits for CI, and executes the merge with the repo's default method or merge queue.

整合多情点分析结果为综合报告，通过去重、分类、排序、总结生成高质量分析。适用于整合多分析源、生成统一报告

Generate AI images, videos, music, and audio from the terminal via muapi.ai — supports 100+ models including Flux, Midjourney v7, Kling 3.0, Veo3, and Suno V5.

Migrates data from MongoDB, PostgreSQL, MySQL, Neo4j, Kafka, and JSONL into SurrealDB with full and incremental CDC synchronization.