Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
Process many issues hands-off in a row: resolve a queue, then run each through the yolo chain under one up-front confirm.
$ npx skills add jepegit/cellpy --skill iflow-cycle -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jepegit/cellpy iflow-cycle --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/jepegit/cellpy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.cursor/skills/iflow-cycle .claude/skills/iflow-cycle && 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 "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .claude/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycleType 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 jepegit/cellpy --skill iflow-cycle -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jepegit/cellpy iflow-cycle --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jepegit/cellpy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.cursor/skills/iflow-cycle .agents/skills/iflow-cycle && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .agents/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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 jepegit/cellpy --skill iflow-cycle -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jepegit/cellpy iflow-cycle --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jepegit/cellpy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.cursor/skills/iflow-cycle .cursor/skills/iflow-cycle && 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 "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .cursor/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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/jepegit/cellpy.git --path .cursor/skills/iflow-cycle--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 jepegit/cellpy --skill iflow-cycle -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jepegit/cellpy iflow-cycle --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jepegit/cellpy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.cursor/skills/iflow-cycle .gemini/skills/iflow-cycle && 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 "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .gemini/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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 jepegit/cellpy iflow-cycleInstalls 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 jepegit/cellpy --skill iflow-cycle -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jepegit/cellpy.git skills-src && mkdir -p .github/skills && cp -r skills-src/.cursor/skills/iflow-cycle .github/skills/iflow-cycle && 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 "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .github/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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 jepegit/cellpy --skill iflow-cycle -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jepegit/cellpy iflow-cycle --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jepegit/cellpy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.cursor/skills/iflow-cycle .opencode/skills/iflow-cycle && 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 "iflow-cycle" agent skill from https://github.com/jepegit/cellpy/tree/master/.cursor/skills/iflow-cycle into .opencode/skills/iflow-cycle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iflow-cycle", 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.
iflow-cycleProcess many issues hands-off in a row: resolve a queue, then run each through the yolo chain under one up-front confirm.
Iflow Cycle is an agent skill from jepegit/cellpy. Process many issues hands-off in a row: resolve a queue, then run each through the yolo chain under one up-front confirm. Stops only when input is strictly necessary.
Its SKILL.md is about 3.5k 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 AI & LLM Engineering, covering Computer vision. The repository describes itself as: extract and tweak data from electrochemical tests of cells. The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit ff2c665. 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.
Shell commands in SKILL.md call:
gitghFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git and gh, which can reach the network depending on how they are called.
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.
Iflow Cycle loads about 3.5k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 1,946 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 jepegit/cellpy at commit ff2c665, republished under its MIT licence (© jepegit). 1,946 words, ~3,534 tokens.
.claude/skills/iflow-cycle/SKILL.md (or your agent's skills folder)./iflow-cycle)Follow this skill to process a queue of issues hands-off, one after another, with a single up-front confirmation — the batch equivalent of /iflow-yolo. Each issue runs the full yolo chain (capture → plan → build → close yolo, PR auto-merged, switch back to default); the cycle interrupts you only when input is strictly necessary.
Use only when every queued issue is genuinely yolo-fit (small, low-risk, well-specified, test-guarded). A queue of risky changes belongs in the individual commands.
12 15 18.yolo — alias for label:yolo: every open issue carrying the configured yolo trigger label (default "yolo"). Case-insensitive. This is the one-token path for “auto-process all yolo issues.”label:<L> — every open issue carrying label <L> (use for labels other than the yolo trigger).epic <N> [stage <k>] — the current stage of epic <N> (or stage <k>).resume — pick up an interrupted cycle from its state file (see Resuming below).onfail:stop (default) / onfail:skip — failure policy (see step 7).max:<n> — raise the safety cap (default 10) for this run.stay — forward stay to each close so the working copy stays on each issue branch (rarely wanted in a cycle).Invoke: type iflow cycle in chat, or /iflow-cycle from the slash menu (iflow-cycle also works).
Profile: reasoning — Prioritize deep thinking and careful trade-offs over speed or token economy.
In Cursor: switch to a thinking-capable model before invoking this step (not Auto-only).
Keep scope tight to what this step requires.
Before any git, gh, or .issueflows/ path operation in this workflow:
Resolution order (stop when unambiguous):
root:<path>, repo:<folder-basename> (directory name, e.g. cellpy-core), or repo:owner/name.issue-flow agent resolve [-C <start>] [--from-file <active-file>] [--json]. Use the returned project_root and repo; pass -C <project_root> to other issue-flow agent … subcommands. When the answer came from the workspace registry, the payload sets resolved_via_workspace_default: true.^\d+- → that root..issueflows/ tree visible in the workspace → that root.issueflow-workspace.toml at the workspace root (created with issue-flow workspace init) may name a default member repo; use it when no scaffold matched above. Tell the user the default was used.After resolution, treat the result as <project_root> and <owner/repo>:
git -C <project_root> … (or issue-flow agent … -C <project_root> for supported ops).gh call — never rely on gh's implicit cwd default. For most commands use --repo <owner/repo>; exception: gh repo view takes the repo as a positional arg (gh repo view <owner/repo> …) and rejects --repo..issueflows/… paths are under <project_root>.When .issueflows/04-designs-and-guides/multi-repo-workspaces.md exists, read it for layout and cross-repo guidance.
Expand aliases. If the queue spec is exactly yolo (case-insensitive), treat it as label:yolo (the baked config value; if .issueflows/config.toml has a different yolo_label than this skill's bake, prefer the live config). Keep the original token in cycle_status.md for humans (queue: yolo → resolved label:yolo).
Resolve the queue. Run issue-flow agent queue --label yolo --json when the alias applied, else issue-flow agent queue <spec> --json (numbers, --label, or --epic). Use its queue (ordered), blocked, and skipped_closed output as the source of truth — do not re-derive the order by hand. If it reports a dependency cycle, stop and show it; nothing runs. If the CLI is unavailable, fall back to reading the issues and ordering by Depends on #N lines yourself, but prefer the CLI. An empty queue → report “nothing to queue” and stop (no confirm needed).
Cap check. If the ordered queue is longer than 10 and the input did not pass max:<n> raising the limit, stop and ask the user to confirm a larger run explicitly. Long unattended runs compound risk.
One consolidated confirm (the only planned interruption). Present, in normal prose:
onfail:stop, the default, or onfail:skip — see step 7);Write the cycle state file. After the confirm, write .issueflows/01-current-issues/cycle_status.md — the durable record that makes the run resumable and visible to /iflow-status. Include: the queue spec, the onfail policy, an ISO timestamp, and the ordered queue as a checklist with one line per issue (- [ ] #<N> — <title> — pending). Update this file as the loop progresses (see step 5); it is a normal tracking file (not an issue<N>_* group), so the folder sweep never touches it.
Per-issue loop. For each issue in order, from a clean default branch:
in-progress in cycle_status.md, then create/switch to its <N>-<slug> branch and follow .cursor/skills/iflow-yolo/SKILL.md verbatim — including its own preflight (refuse on default branch, refuse with dirty unrelated changes, tests pass up front) and its consolidated-confirm step, which the up-front batch confirm in step 3 satisfies (do not re-ask per issue).cycle_status.md (- [x] #<N> — <title> — merged <PR-url>) and continue to the next issue.Strictly-necessary-input rule. Between issues the cycle runs unattended. Stop and ask only when:
a. tests or lint fail in a way you cannot fix within the current issue's scope;
b. a merge is refused, or a sync with the default branch will not complete — but a refusal whose only conflict is additive HISTORY.md bullets is not a stop: close's sync step (issue-flow agent sync-branch) resolves that and retries the merge once. Stop only when the sync itself exits 1, or the retry is refused again;
c. the issue spec is ambiguous, contradictory, or turns out not small (yolo's scope check aborts);
d. an action would fall outside the confirmed queue (touching an unlisted issue, an unrelated dirty file, a destructive op).
Anything else — routine implementation choices, passing tests, clean merges — proceeds without asking.
Failure policy (from the onfail: token; default stop). When a stop condition (step 6) trips on an issue:
onfail:stop (default) — halt the cycle: finish no further issues, leave the repo on the default branch, clean (the in-flight issue's branch stays as-is for the user to inspect), record the stop reason and the not-reached issues in cycle_status.md, and report. Do not attempt the rest of the queue.onfail:skip — park and continue: record the failure against that issue in cycle_status.md (- [~] #<N> — <title> — failed: <reason>), park its work per .cursor/skills/iflow-pause/SKILL.md conventions (status note + move to 02-partly-solved-issues/), return to a clean default branch, and proceed to the next queued issue. A skip never bypasses a yolo safeguard — it records the trip and moves on.Finish. When the queue is exhausted (or halted), finalize cycle_status.md (mark it - [x] Done) and move it to .issueflows/03-solved-issues/cycle_status_<YYYY-MM-DD>.md so it is archived, not re-detected as in-flight.
Batch report. Summarize the whole run: per issue — number, title, PR URL, merge result (merged / queued via --auto / failed-and-skipped / not reached), and duration if tracked; then the queue items skipped (closed), blocked (with blockers), and — on a halt — the stop reason and which issues were not reached.
/iflow-cycle resume picks up an interrupted cycle:
.issueflows/01-current-issues/cycle_status.md. If it is missing, tell the user there is no in-flight cycle and stop.pending / in-progress) and re-verify them with issue-flow agent queue <original-spec> --json — an issue that has since closed, or become blocked, is dropped/deferred with a note (state can move while a cycle is paused).onfail policy recorded in the file.By default the cycle is sequential — one issue fully lands before the next starts. When the input passes parallel:<n> and the harness supports background execution, provably independent issues may run concurrently (up to n at a time). This is experimental; the sequential path above is always the default and is never weakened to enable it.
issue-flow agent queue's independent list — issues with no dependency relation (either direction) to any other queue member. Everything else runs sequentially.parallel:<n> and run sequentially — never pretend to parallelize.git worktree add ../<repo>-<N> <N>-<slug> so each issue has an isolated tree; run the yolo work there.worktree add, run issue-flow agent open-workspace <worktree-path> --json (print-only) and show the path. Do not launch a window. Continue with worktree-only parallel — see .issueflows/04-designs-and-guides/separate-workspaces.md.HISTORY.md; each leaves its changelog bullet in its issue status file / PR body, and the coordinator appends them in merge order during the serial merge step — same ordering rule as the changelog resolver (already-landed bullets first, the newest last), so serial and parallel runs produce the same file. If a worker PR does go DIRTY on [Unreleased], the coordinator resolves it with issue-flow agent sync-branch rather than hand-editing markers.When in doubt, prefer the sequential run — parallel dispatch trades safety for speed and every one of the rules above must hold.
/iflow-cycle yolo (or label:yolo) is the supported way to
auto-process every open yolo-labelled issue. No separate batch skill.
Conflict stance (sequential default): each issue's yolo close merges its PR
and returns to a clean default branch before the next issue starts, so
within the cycle shared files (HISTORY.md, etc.) stay single-writer.
Stop-on-fail leaves the tree clean on default.
That single-writer property does not protect against the default branch
moving externally — another session or an already-open PR merging while one
queued issue is in its test/CI window. The collision is almost always the same:
two additive bullets under ## [Unreleased]. Close's sync step owns that
(issue-flow agent sync-branch: rebase onto origin/<default>, keep both
bullet sets with the in-flight one last, force-with-lease push, retry the merge
once), so a changelog-only conflict no longer halts a batch. Everything else
still trips step 6b. For experimental concurrent work, see
Parallel dispatch above and .issueflows/04-designs-and-guides/parallel-cycle.md
(merges stay serialized there too). Labelling first is optional via
/iflow-review yolo — then run /iflow-cycle yolo.
/iflow never auto-dispatches to /iflow-cycle; it is an explicit, deliberate batch action.parallel:<n>) is opt-in and experimental; refusing it must always leave a working sequential run./iflow-cleanup from this skill; batch branch deletion still needs the user to see the merged PRs first.cycle_status.md is the single source of truth for an in-flight cycle: keep it current so resume and /iflow-status stay accurate. It is not an issue<N>_* group, so the folder sweep leaves it alone; archive it (step 8) when the run ends.© jepegit, 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 .cursor/skills/iflow-cycle of jepegit/cellpy.
Open the folder on GitHubat commit ff2c665
Iflow Cycle 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 |
|---|---|---|---|---|---|---|
| Iflow Cycle this skilljepegit/cellpy | 109 | — | ~3.5k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.3k | Automated safety check: Pass | MIT | |
| CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Yolo Master AgentTencent/YOLO-Master | 742 | — | ~755 | Automated safety check: Pass | AGPL-3.0 | |
| Video Understandjjyaoao/HelloAgents | 3.2k | 1 repos | ~6.2k | Automated safety check: Pass | MIT | |
| Motioneyes Visual Analysisedwardsanchez/MotionEyes | 229 | — | ~2k | Automated safety check: Pass | None |
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
Orchestra-Research/AI-Research-SKILLs
Explains OpenAI's CLIP model for zero-shot image classification, image-text similarity, semantic image search and content moderation, with install steps and code patterns.
Tencent/YOLO-Master
A skill your agent uses when the user wants to run a YOLO-Master task (train/val/predict/track/export/benchmark) or use the Agent Skill dispatcher.
jjyaoao/HelloAgents
Implement specialized video understanding capabilities using the z-ai-web-dev-sdk.
edwardsanchez/MotionEyes
Pixel-based motion and UI change analysis from frame sequences or screenshots using computer vision and visual comparison.
Orchestra-Research/AI-Research-SKILLs
Guide to LLaVA for image chat, visual question answering and captioning, with model sizes, CLI and Gradio usage and multi-turn conversation code.
jepegit/cellpy
Use GitHub CLI to snapshot or wait on CI for a pull request or workflow run.
jepegit/cellpy
Respond in a terse "smart caveman" style that keeps all technical substance but drops filler, articles, and pleasantries.
jepegit/cellpy
Interview the user relentlessly about a plan or design until every branch of the decision tree is resolved, then feed the conclusions into the issue plan.
jepegit/cellpy
Condense old solved issue groups into one dated summary file, then delete the originals.
jepegit/cellpy
Capture a GitHub issue locally as issue<numberoriginal.md and archive other current issues by done status.
jepegit/cellpy
Triage a GitHub issue's comment thread into the curated, bucketed summary section of issue<Noriginal.md.
Categories
Process many issues hands-off in a row: resolve a queue, then run each through the yolo chain under one up-front confirm. Iflow Cycle is an agent skill from jepegit/cellpy. Process many issues hands-off in a row: resolve a queue, then run each through the yolo chain under one up-front confirm.
Iflow Cycle fits situations like: tasks that involve Computer vision.
Run `npx skills add jepegit/cellpy --skill iflow-cycle -a claude-code`. Or copy the skill folder (.cursor/skills/iflow-cycle in jepegit/cellpy) into .claude/skills/iflow-cycle in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jepegit/cellpy --skill iflow-cycle -a codex`. Or copy the skill folder (.cursor/skills/iflow-cycle in jepegit/cellpy) into .agents/skills/iflow-cycle 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 jepegit/cellpy --skill iflow-cycle -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iflow-cycle, .gemini/skills/iflow-cycle, .github/skills/iflow-cycle and .opencode/skills/iflow-cycle in your project.
Going by SKILL.md and its folder, Iflow Cycle needs the command-line tools its instructions call (git and gh).
SKILL.md contains no URLs. Its commands use git and gh, which can reach the network depending on how they are called. 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.
Iflow Cycle is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k 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 Iflow Cycle: Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Yolo Master Agent (Tencent/YOLO-Master, 742 stars) and Video Understand (jjyaoao/HelloAgents, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jepegit (a GitHub user) maintains it in jepegit/cellpy, which has 109 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on October 6, 2026.
Source: jepegit/cellpy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.