Taisly Social Media Posting
taisly/agent
Free AI-first short-form video publishing to TikTok, Instagram Reels, YouTube Shorts, X, and Facebook from AI agents through Taisly.
Tightening one long single-take recording — talking-head, screencast, tutorial, podcast video — by removing dead air in the DaVinci Resolve MCP.
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recording --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .claude/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .claude/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recordingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recording --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .agents/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .agents/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recording --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .cursor/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .cursor/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/samuelgursky/davinci-resolve-mcp.git --path .agents/skills/resolve-tighten-recording--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recording --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .gemini/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .gemini/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recordingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .github/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .github/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install samuelgursky/davinci-resolve-mcp resolve-tighten-recording --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/resolve-tighten-recording .opencode/skills/resolve-tighten-recording && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "resolve-tighten-recording" agent skill from https://github.com/samuelgursky/davinci-resolve-mcp/tree/main/.agents/skills/resolve-tighten-recording into .opencode/skills/resolve-tighten-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "resolve-tighten-recording", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
resolve-tighten-recordingTightening one long single-take recording — talking-head, screencast, tutorial, podcast video — by removing dead air in the DaVinci Resolve MCP.
Resolve Tighten Recording is an agent skill from samuelgursky/davinci-resolve-mcp. Tightening one long single-take recording — talking-head, screencast, tutorial, podcast video — by removing dead air in the DaVinci Resolve MCP. Apply when asked to tighten a recording, remove silences or dead air, cut the pauses out of a long take, or turn a raw one-take recording into a first cut. The subtractive counterpart to resolve-rough-cut, which selects shots from many clips; this skill removes time from one clip.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering MCP servers. It works with Model Context Protocol. The repository describes itself as: MCP server integration for DaVinci Resolve Studio. The licence is MIT.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 8911bd2. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Resolve Tighten Recording loads about 2.2k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 1,115 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from samuelgursky/davinci-resolve-mcp at commit 8911bd2, republished under its MIT licence (© samuelgursky). 1,115 words, ~2,171 tokens.
.claude/skills/resolve-tighten-recording/SKILL.md (or your agent's skills folder).Turns one long raw take into a tightened variant timeline. The variant is the deliverable; the original timeline is never touched.
Everything below was measured live against Resolve Studio 21.0.1.11 / MCP v2.80.1 on 2026-08-06, on a real 28.5-minute 30fps screen recording, unless a different date is given.
Deliver a tightened variant timeline, plan → review → confirm. Do not grade, caption, or add anything; a tighten is pure subtraction. The variant runs generous on purpose — recovering over-cut material is slow and invisible, trimming further is fast and visible.
Two things always go back to the editor with the variant:
Lift the analysis caps for long media —
media_analysis set_caps_preset {preset: "unlimited"}. The standard preset
carries a 90-second wall clock; multi-hour material dies on it. Restore
standard when done (step 7).
Transcribe — media_analysis start_batch_job with
{clip_id, vision: false, transcription: {enabled: true, ...}}, then
run_batch_job_slice {job_id}. Two traps in one call pair:
start_batch_job returns a
durable job in queued and nothing runs until a slice call drives it.run_batch_job_slice blocks until the slice completes — budget
roughly 4-7x realtime for local whisper (measured: 28.5min of Chinese
speech in 5m14s via mlx_whisper) and run it from a background process,
not the main conversation.Copy clip_id from media_pool probe_media_pool output. Never type it
from memory: one transposed hex pair (measured 2026-06: b9ab → 9bab)
fails every downstream call in ways that look like engine bugs.
Plan — edit_engine plan_tighten {timeline_name}. Dry run; nothing
moves. min_pause_seconds raises the bar when the default cuts too
fine-grained. The plan persists on disk — planning and executing in
different sessions is fine.
Review with the editor: lift count, estimated removed seconds, and the largest lifts (sorted by duration). This is the approval gate the whole tool sequence exists for — do not skip it because the numbers look reasonable.
Execute — edit_engine execute_tighten {plan_id} returns a
confirm_token (TTL 300s); re-call with the token. Both calls in the
same MCP session is verified; a token across a server restart is not —
don't bet on it.
Verify, in this order:
timeline detect_gaps_overlaps on the variant → must be 0 / 0.readback.after.clip_count in the execute response ≈ 2× the video
keep-range count when audio is mirrored (113 video + 113 audio = 226
measured). If it equals the video count alone, the variant is silent —
stop and say so.timeline clip_where {track_type, track_index}
against the plan's keep ranges (coordinate rules below). clip_where
reads the current timeline only — set_current to the variant first;
it takes no timeline_name argument.Clean up — restore set_caps_preset {preset: "standard"},
project_manager save, and list timelines: execute_tighten archives the
source timeline once (_versioning.archived: true, by design), so a
*_archived_vNN appears. Surface it; deleting is the editor's call.
The plan and the execute response describe ranges in different coordinate systems, and both look like plausible frame pairs:
| Field | Coordinate system | Verified |
|---|---|---|
plan keep_ranges start_frame/end_frame | Source frames, end_frame exclusive (duration = end − start) | frame-exact against clip_where readback |
structural_diff.added in_frame/out_frame | Record (timeline) frames of the variant | matches variant item record spans, not source spans |
| variant record positions | cumulative sum of keep-range durations | record[i] = Σ(end−start)(j<i), frame-exact |
Feeding structural_diff.added numbers anywhere a source range is expected
places every clip at the wrong moment of the right file — cut lengths stay
correct, nothing errors, and the timeline renders. When any endpoint semantics
are in doubt, place one range, read it back with clip_where, verify
position + duration + source span, then batch the rest.
A camera track stacked over a screen-capture track (V1 + V2, same session) is
common for tutorials. execute_tighten assembles only the analyzed
source; the other layer is dropped from the variant, silently. To rebuild it:
keep_ranges (source frames), add the offset, and append
with media_pool append_to_timeline clip_infos:
{clip_id, start_frame, end_frame, record_frame, record_frame_mode: "absolute", track_index: 2, media_type: 1} (media_type: 1 = video only;
keep the analyzed layer's audio).Multicam compound clips do not reach the transcription engine at all — a tighten on multicam material silently skips it. Keep plain stacked tracks and use the recipe above instead.
plan_tighten measures the microphone, not the meaning. Three classes
survive every threshold, and each needs a different instrument:
plan_transcript_tighten covers
these at word level (fillers, immediate ≤4-word restarts under 0.6s,
collapsible pauses) and emits the same keep_ranges shape. Note its filler
set is English hesitation words; other languages pass through unflagged.Report all three as known limits when handing over the variant, instead of letting the tightened timeline imply "everything removable was removed".
detect_gaps_overlaps alone — it proves the assembly is gapless,
not that the right frames were kept. Duration check and spot placement
reads are part of verification, not extras.tightened, dead-air pass, a version tag) so a project with several
passes stays readable.min_pause_seconds
and review the big lifts instead.unlimited after the run.The tighten pipeline reads source media and writes analysis artifacts to the analysis root only. The variant references existing Media Pool items — no transcode, no proxy, no relink, and the original timeline is archived by the tool, never mutated.
© samuelgursky, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/resolve-tighten-recording of samuelgursky/davinci-resolve-mcp.
Open the folder on GitHubat commit 8911bd2
Resolve Tighten Recording next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Resolve Tighten Recording this skillsamuelgursky/davinci-resolve-mcp | 3.5k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Taisly Social Media Postingtaisly/agent | 217 | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Clipmivo VideoBarneyD66/clipmivo-tools | 142 | — | ~945 | Automated safety check: Pass | MIT | |
| Final Cut ProDareDev256/fcp-mcp-server | 121 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Audio Playbacksonilo-ai/skills | 115 | — | ~813 | Automated safety check: Notes | MIT | |
| Wjs Voicedropjianshuo/claude-skills | 131 | — | ~918 | Automated safety check: Pass | MIT |
taisly/agent
Free AI-first short-form video publishing to TikTok, Instagram Reels, YouTube Shorts, X, and Facebook from AI agents through Taisly.
BarneyD66/clipmivo-tools
Create and manage AI video tasks through ClipmivoAI using its MCP server, CLI or REST API.
DareDev256/fcp-mcp-server
Edit Final Cut Pro timelines with natural language via FCPXML.
sonilo-ai/skills
Play a local audio file through the system's default speakers using Sonilo's MCP server.
jianshuo/claude-skills
VoiceDrop 的入口。所有能力都在 MCP 里(voicedrop.cn/mcp,44 个工具:文章读写与版本、文风与蒸馏、挖矿与重写、社区与投币、算力、分享/公众号/小红书、书架读书与写书修书)。本 skill 只做一件事——把你接上那个 MCP:用它的 login 工具做 6+4 手机配对登录拿到令牌,然后接进客户端。触发词:"voicedrop"、"登录…
glebis/claude-skills
This skill should be used when the user wants to view, review, rate, organize, search, or export images / AI-art generations with the Cull app.
samuelgursky/davinci-resolve-mcp
Orientation and index for DaVinci Resolve MCP work — grading, editing, conforming, delivery, media analysis, and .drp/.drt/.drx file work, live in a running Resolve or offline with none open.
samuelgursky/davinci-resolve-mcp
Assembling a short-form social rough cut from raw behind-the-scenes or vlog footage in the DaVinci Resolve MCP.
samuelgursky/davinci-resolve-mcp
The editorial and finishing preferences this project's work is judged against — cut rhythm, shot selection, delivery conventions, and the corrections that have already been given.
samuelgursky/davinci-resolve-mcp
Audio and Fairlight work in the DaVinci Resolve MCP. An agent skill from samuelgursky/davinci-resolve-mcp.
samuelgursky/davinci-resolve-mcp
Color grading and look work in the DaVinci Resolve MCP. An agent skill from samuelgursky/davinci-resolve-mcp.
samuelgursky/davinci-resolve-mcp
Conforming, relinking, and finishing prep in the DaVinci Resolve MCP.
Works with
Categories
Tightening one long single-take recording — talking-head, screencast, tutorial, podcast video — by removing dead air in the DaVinci Resolve MCP. Resolve Tighten Recording is an agent skill from samuelgursky/davinci-resolve-mcp. Tightening one long single-take recording — talking-head, screencast, tutorial, podcast video — by removing dead air in the DaVinci Resolve MCP.
Resolve Tighten Recording fits situations like: tasks that involve MCP servers.
Run `npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a claude-code`. Or copy the skill folder (.agents/skills/resolve-tighten-recording in samuelgursky/davinci-resolve-mcp) into .claude/skills/resolve-tighten-recording in your project. Claude Code loads it when a task matches its description.
Run `npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a codex`. Or copy the skill folder (.agents/skills/resolve-tighten-recording in samuelgursky/davinci-resolve-mcp) into .agents/skills/resolve-tighten-recording in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/resolve-tighten-recording, .gemini/skills/resolve-tighten-recording, .github/skills/resolve-tighten-recording and .opencode/skills/resolve-tighten-recording in your project.
SKILL.md names no scripts, command-line tools or credentials: Resolve Tighten Recording is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Resolve Tighten Recording is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Resolve Tighten Recording: Taisly Social Media Posting (taisly/agent, 217 stars), Clipmivo Video (BarneyD66/clipmivo-tools, 142 stars), Final Cut Pro (DareDev256/fcp-mcp-server, 121 stars) and Audio Playback (sonilo-ai/skills, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
samuelgursky (a GitHub user) maintains it in samuelgursky/davinci-resolve-mcp, which has 3,461 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 10, 2026.
Source: samuelgursky/davinci-resolve-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.