Skill Seekers Builder
yusufkaraaslan/Skill_Seekers
Detects the type of a knowledge source and uses the Skill Seekers MCP tools to turn docs, repos, PDFs or videos into packaged AI skills.
Agent skill for swarm-issue - invoke with $agent-swarm-issue
$ npx skills add ruvnet/ruflo --skill agent-swarm-issue -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ruvnet/ruflo agent-swarm-issue --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/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .claude/skills/agent-swarm-issue && 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 "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .claude/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issueType 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 ruvnet/ruflo --skill agent-swarm-issue -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ruvnet/ruflo agent-swarm-issue --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .agents/skills/agent-swarm-issue && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .agents/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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 ruvnet/ruflo --skill agent-swarm-issue -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ruvnet/ruflo agent-swarm-issue --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .cursor/skills/agent-swarm-issue && 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 "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .cursor/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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/ruvnet/ruflo.git --path .agents/skills/agent-swarm-issue--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 ruvnet/ruflo --skill agent-swarm-issue -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ruvnet/ruflo agent-swarm-issue --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .gemini/skills/agent-swarm-issue && 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 "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .gemini/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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 ruvnet/ruflo agent-swarm-issueInstalls 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 ruvnet/ruflo --skill agent-swarm-issue -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .github/skills/agent-swarm-issue && 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 "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .github/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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 ruvnet/ruflo --skill agent-swarm-issue -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ruvnet/ruflo agent-swarm-issue --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .opencode/skills/agent-swarm-issue && 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 "agent-swarm-issue" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-issue into .opencode/skills/agent-swarm-issue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-issue", 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.
agent-swarm-issueAgent skill for swarm-issue - invoke with $agent-swarm-issue
Agent Swarm Issue is an agent skill from ruvnet/ruflo. Agent skill for swarm-issue - invoke with $agent-swarm-issue
Its SKILL.md is about 3.6k 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 Agent Workflows, covering Multi-agent orchestration. It works with GitHub and Model Context Protocol. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.
12 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 58e0ae7. 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:
npxghjqFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx 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.
Agent Swarm Issue loads about 3.6k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 327 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 ruvnet/ruflo at commit 58e0ae7, republished under its MIT licence (© ruvnet). 327 words, ~3,610 tokens.
.claude/skills/agent-swarm-issue/SKILL.md (or your agent's skills folder).name: swarm-issue description: GitHub issue-based swarm coordination agent that transforms issues into intelligent multi-agent tasks with automatic decomposition and progress tracking type: coordination color: "#FF6B35" tools:
Transform GitHub Issues into intelligent swarm tasks, enabling automatic task decomposition and agent coordination with advanced multi-agent orchestration.
# Create swarm from issue using gh CLI
# Get issue details
ISSUE_DATA=$(gh issue view 456 --json title,body,labels,assignees,comments)
# Create swarm from issue
npx ruv-swarm github issue-to-swarm 456 \
--issue-data "$ISSUE_DATA" \
--auto-decompose \
--assign-agents
# Batch process multiple issues
ISSUES=$(gh issue list --label "swarm-ready" --json number,title,body,labels)
npx ruv-swarm github issues-batch \
--issues "$ISSUES" \
--parallel
# Update issues with swarm status
echo "$ISSUES" | jq -r '.[].number' | while read -r num; do
gh issue edit $num --add-label "swarm-processing"
doneExecute swarm operations via issue comments:
<!-- In issue comment -->
$swarm analyze
$swarm decompose 5
$swarm assign @agent-coder
$swarm estimate
$swarm start<!-- .github/ISSUE_TEMPLATE$swarm-task.yml -->
name: Swarm Task
description: Create a task for AI swarm processing
body:
- type: dropdown
id: topology
attributes:
label: Swarm Topology
options:
- mesh
- hierarchical
- ring
- star
- type: input
id: agents
attributes:
label: Required Agents
placeholder: "coder, tester, analyst"
- type: textarea
id: tasks
attributes:
label: Task Breakdown
placeholder: |
1. Task one description
2. Task two description// .github$swarm-labels.json
{
"rules": [
{
"keywords": ["bug", "error", "broken"],
"labels": ["bug", "swarm-debugger"],
"agents": ["debugger", "tester"]
},
{
"keywords": ["feature", "implement", "add"],
"labels": ["enhancement", "swarm-feature"],
"agents": ["architect", "coder", "tester"]
},
{
"keywords": ["slow", "performance", "optimize"],
"labels": ["performance", "swarm-optimizer"],
"agents": ["analyst", "optimizer"]
}
]
}# Assign agents based on issue content
npx ruv-swarm github issue-analyze 456 \
--suggest-agents \
--estimate-complexity \
--create-subtasks# Create swarm with full issue context using gh CLI
# Get complete issue data
ISSUE=$(gh issue view 456 --json title,body,labels,assignees,comments,projectItems)
# Get referenced issues and PRs
REFERENCES=$(gh issue view 456 --json body --jq '.body' | \
grep -oE '#[0-9]+' | while read -r ref; do
NUM=${ref#\#}
gh issue view $NUM --json number,title,state 2>$dev$null || \
gh pr view $NUM --json number,title,state 2>$dev$null
done | jq -s '.')
# Initialize swarm
npx ruv-swarm github issue-init 456 \
--issue-data "$ISSUE" \
--references "$REFERENCES" \
--load-comments \
--analyze-references \
--auto-topology
# Add swarm initialization comment
gh issue comment 456 --body "🐝 Swarm initialized for this issue"# Break down issue into subtasks with gh CLI
# Get issue body
ISSUE_BODY=$(gh issue view 456 --json body --jq '.body')
# Decompose into subtasks
SUBTASKS=$(npx ruv-swarm github issue-decompose 456 \
--body "$ISSUE_BODY" \
--max-subtasks 10 \
--assign-priorities)
# Update issue with checklist
CHECKLIST=$(echo "$SUBTASKS" | jq -r '.tasks[] | "- [ ] " + .description')
UPDATED_BODY="$ISSUE_BODY
## Subtasks
$CHECKLIST"
gh issue edit 456 --body "$UPDATED_BODY"
# Create linked issues for major subtasks
echo "$SUBTASKS" | jq -r '.tasks[] | select(.priority == "high")' | while read -r task; do
TITLE=$(echo "$task" | jq -r '.title')
BODY=$(echo "$task" | jq -r '.description')
gh issue create \
--title "$TITLE" \
--body "$BODY
Parent issue: #456" \
--label "subtask"
done# Update issue with swarm progress using gh CLI
# Get current issue state
CURRENT=$(gh issue view 456 --json body,labels)
# Get swarm progress
PROGRESS=$(npx ruv-swarm github issue-progress 456)
# Update checklist in issue body
UPDATED_BODY=$(echo "$CURRENT" | jq -r '.body' | \
npx ruv-swarm github update-checklist --progress "$PROGRESS")
# Edit issue with updated body
gh issue edit 456 --body "$UPDATED_BODY"
# Post progress summary as comment
SUMMARY=$(echo "$PROGRESS" | jq -r '
"## 📊 Progress Update
**Completion**: \(.completion)%
**ETA**: \(.eta)
### Completed Tasks
\(.completed | map("- ✅ " + .) | join("\n"))
### In Progress
\(.in_progress | map("- 🔄 " + .) | join("\n"))
### Remaining
\(.remaining | map("- ⏳ " + .) | join("\n"))
---
🤖 Automated update by swarm agent"')
gh issue comment 456 --body "$SUMMARY"
# Update labels based on progress
if [[ $(echo "$PROGRESS" | jq -r '.completion') -eq 100 ]]; then
gh issue edit 456 --add-label "ready-for-review" --remove-label "in-progress"
fi# Handle issue dependencies
npx ruv-swarm github issue-deps 456 \
--resolve-order \
--parallel-safe \
--update-blocking# Coordinate epic-level swarms
npx ruv-swarm github epic-swarm \
--epic 123 \
--child-issues "456,457,458" \
--orchestrate# Generate issue from swarm analysis
npx ruv-swarm github create-issues \
--from-analysis \
--template "bug-report" \
--auto-assign# .github$workflows$issue-swarm.yml
name: Issue Swarm Handler
on:
issues:
types: [opened, labeled, commented]
jobs:
swarm-process:
runs-on: ubuntu-latest
steps:
- name: Process Issue
uses: ruvnet$swarm-action@v1
with:
command: |
if [[ "${{ github.event.label.name }}" == "swarm-ready" ]]; then
npx ruv-swarm github issue-init ${{ github.event.issue.number }}
fi# Sync with project board
npx ruv-swarm github issue-board-sync \
--project "Development" \
--column-mapping '{
"To Do": "pending",
"In Progress": "active",
"Done": "completed"
}'# Specialized bug handling
npx ruv-swarm github bug-swarm 456 \
--reproduce \
--isolate \
--fix \
--test# Feature implementation swarm
npx ruv-swarm github feature-swarm 456 \
--design \
--implement \
--document \
--demo# Refactoring swarm
npx ruv-swarm github debt-swarm 456 \
--analyze-impact \
--plan-migration \
--execute \
--validate# Process stale issues with swarm using gh CLI
# Find stale issues
STALE_DATE=$(date -d '30 days ago' --iso-8601)
STALE_ISSUES=$(gh issue list --state open --json number,title,updatedAt,labels \
--jq ".[] | select(.updatedAt < \"$STALE_DATE\")")
# Analyze each stale issue
echo "$STALE_ISSUES" | jq -r '.number' | while read -r num; do
# Get full issue context
ISSUE=$(gh issue view $num --json title,body,comments,labels)
# Analyze with swarm
ACTION=$(npx ruv-swarm github analyze-stale \
--issue "$ISSUE" \
--suggest-action)
case "$ACTION" in
"close")
# Add stale label and warning comment
gh issue comment $num --body "This issue has been inactive for 30 days and will be closed in 7 days if there's no further activity."
gh issue edit $num --add-label "stale"
;;
"keep")
# Remove stale label if present
gh issue edit $num --remove-label "stale" 2>$dev$null || true
;;
"needs-info")
# Request more information
gh issue comment $num --body "This issue needs more information. Please provide additional context or it may be closed as stale."
gh issue edit $num --add-label "needs-info"
;;
esac
done
# Close issues that have been stale for 37+ days
gh issue list --label stale --state open --json number,updatedAt \
--jq ".[] | select(.updatedAt < \"$(date -d '37 days ago' --iso-8601)\") | .number" | \
while read -r num; do
gh issue close $num --comment "Closing due to inactivity. Feel free to reopen if this is still relevant."
done# Automated triage system
npx ruv-swarm github triage \
--unlabeled \
--analyze-content \
--suggest-labels \
--assign-priority# Find duplicate issues
npx ruv-swarm github find-duplicates \
--threshold 0.8 \
--link-related \
--close-duplicates# Link issues to PRs automatically
npx ruv-swarm github link-pr \
--issue 456 \
--pr 789 \
--update-both# Coordinate milestone swarms
npx ruv-swarm github milestone-swarm \
--milestone "v2.0" \
--parallel-issues \
--track-progress# Handle issues across repositories
npx ruv-swarm github cross-repo \
--issue "org$repo#456" \
--related "org$other-repo#123" \
--coordinate# Analyze swarm performance
npx ruv-swarm github issue-metrics \
--issue 456 \
--metrics "time-to-close,agent-efficiency,subtask-completion"# Generate effectiveness report
npx ruv-swarm github effectiveness \
--issues "closed:>2024-01-01" \
--compare "with-swarm,without-swarm"# Issue #789: Memory leak in production
npx ruv-swarm github issue-init 789 \
--topology hierarchical \
--agents "debugger,analyst,tester,monitor" \
--priority critical \
--reproduce-steps# Issue #234: Add OAuth integration
npx ruv-swarm github issue-init 234 \
--topology mesh \
--agents "architect,coder,security,tester" \
--create-design-doc \
--estimate-effort# Issue #567: Update API documentation
npx ruv-swarm github issue-init 567 \
--topology ring \
--agents "researcher,writer,reviewer" \
--check-links \
--validate-examples# Initialize issue-specific swarm with optimal topology
mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 8 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__claude-flow__agent_spawn { type: "analyst", name: "Issue Analyzer" }
mcp__claude-flow__agent_spawn { type: "coder", name: "Solution Developer" }
mcp__claude-flow__agent_spawn { type: "tester", name: "Validation Engineer" }
# Store issue context in swarm memory
mcp__claude-flow__memory_usage {
action: "store",
key: "issue/#{issue_number}$context",
value: { title: "issue_title", labels: ["labels"], complexity: "high" }
}
# Orchestrate issue resolution workflow
mcp__claude-flow__task_orchestrate {
task: "Coordinate multi-agent issue resolution with progress tracking",
strategy: "adaptive",
priority: "high"
}// Pre-hook: Issue Analysis and Swarm Setup
const preHook = async (issue) => {
// Initialize swarm with issue-specific topology
const topology = determineTopology(issue.complexity);
await mcp__claude_flow__swarm_init({ topology, maxAgents: 6 });
// Store issue context for swarm agents
await mcp__claude_flow__memory_usage({
action: "store",
key: `issue/${issue.number}$metadata`,
value: { issue, analysis: await analyzeIssue(issue) }
});
};
// Post-hook: Progress Updates and Coordination
const postHook = async (results) => {
// Update issue with swarm progress
await updateIssueProgress(results);
// Generate follow-up tasks
await createFollowupTasks(results.remainingWork);
// Store completion metrics
await mcp__claude_flow__memory_usage({
action: "store",
key: `issue/${issue.number}$completion`,
value: { metrics: results.metrics, timestamp: Date.now() }
});
};See also: swarm-pr.md, sync-coordinator.md, workflow-automation.md
© ruvnet, 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/agent-swarm-issue of ruvnet/ruflo.
Open the folder on GitHubat commit 58e0ae7
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.
Agent Swarm Issue 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 |
|---|---|---|---|---|---|---|
| Agent Swarm Issue this skillruvnet/ruflo | 74k | 2 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Skill Seekers Builderyusufkaraaslan/Skill_Seekers | 15k | — | ~760 | Automated safety check: Pass | MIT | |
| Codex with ChatGPT Planning LoopXiaoDuoYa/codex-with-chatgpt | 7.1k | — | ~11k | Automated safety check: Notes | MIT | |
| MemPalace Task HandoffMemPalace/mempalace | 59k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Context Mode Opsmksglu/context-mode | 26k | — | ~6k | Automated safety check: Pass | Custom licence | |
| Helmor CLIdohooo/helmor | 1.3k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 |
yusufkaraaslan/Skill_Seekers
Detects the type of a knowledge source and uses the Skill Seekers MCP tools to turn docs, repos, PDFs or videos into packaged AI skills.
XiaoDuoYa/codex-with-chatgpt
Uses ChatGPT in the browser as the planning and review brain for a Codex session, with Codex keeping all execution and ChatGPT reading the workspace through a bridge.
MemPalace/mempalace
Creates, hands off, claims, executes and closes agent tasks through the MemPalace logstream, with approval of the exact task before it is recorded.
mksglu/context-mode
Runs maintenance for the context-mode project with parallel subagents: issue triage, PR review, releases, bug fixes, announcements and branch syncing.
dohooo/helmor
Use the Helmor CLI to remote-control Helmor from the terminal.
zhu1090093659/deepseek-pp
Automates pre-development workflow for large-scale complex tasks.
ruvnet/ruflo
Stores, searches, and retrieves successful patterns with HNSW-indexed semantic search so agents can reuse past solutions instead of relearning them.
ruvnet/ruflo
Runs claude-flow CLI security scans for input validation, path traversal, SQL injection, XSS, hardcoded secrets and known CVEs, and writes an audit report.
ruvnet/ruflo
Applies the SPARC method (specification, pseudocode, architecture, refinement, completion) with 17 specialized modes and multi-agent orchestration, from research to deployment.
ruvnet/ruflo
Coordinates a hierarchical swarm of specialized agents through the claude-flow CLI for work that spans several files or modules at once.
ruvnet/ruflo
Sets up and drives Ruflo, an npm-installed orchestration layer for multi-agent swarms, persistent memory, routing, hooks and its MCP tool catalog.
ruvnet/ruflo
Reference for spawning, listing, monitoring and stopping agents with claude-flow commands, with agent type families, routing codes and coordination tips.
Works with
Categories
Agent skill for swarm-issue - invoke with $agent-swarm-issue. Agent Swarm Issue is an agent skill from ruvnet/ruflo.
Agent Swarm Issue fits situations like: tasks that involve Multi-agent orchestration.
Run `npx skills add ruvnet/ruflo --skill agent-swarm-issue -a claude-code`. Or copy the skill folder (.agents/skills/agent-swarm-issue in ruvnet/ruflo) into .claude/skills/agent-swarm-issue in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ruvnet/ruflo --skill agent-swarm-issue -a codex`. Or copy the skill folder (.agents/skills/agent-swarm-issue in ruvnet/ruflo) into .agents/skills/agent-swarm-issue 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 ruvnet/ruflo --skill agent-swarm-issue -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-swarm-issue, .gemini/skills/agent-swarm-issue, .github/skills/agent-swarm-issue and .opencode/skills/agent-swarm-issue in your project.
Going by SKILL.md and its folder, Agent Swarm Issue needs the command-line tools its instructions call (npx, gh and jq). Our summary lists: Node.js.
SKILL.md contains no URLs. Its commands use npx 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.
Agent Swarm Issue is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k 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 Agent Swarm Issue: Skill Seekers Builder (yusufkaraaslan/Skill_Seekers, 15k stars), Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), MemPalace Task Handoff (MemPalace/mempalace, 59k stars) and Context Mode Ops (mksglu/context-mode, 26k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,159 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 9, 2026.
Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.