swarm-coding
Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for complex, multi-system, or orthogonal engineering initiatives (e.g., concurrent backend, frontend, database, QA). Manages hierarchical Lead Agents and Specialists, disjoint work allocations, a
Asset-Profil
Coding- und Entwickler-Agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Szenario
Testing and QA
I need my agent to test a web app, reproduce bugs, and verify fixes.
Agent-Fit
Claude Code + CLI + Codex
Geeignet für Codex, Claude Code, Cursor, CLI oder benutzerdefinierte Agents.
Installieren
Bereit
npx skills add danicat/skills --skill swarm-coding
Wartung
Aktuell
Heute gepusht
Risiko
Prüfung nötig
Dependency or permission surface needs review
GitHub-Qualität
16
59/100 Qualität · 61/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent-Adoptionskarte
Vertrauen, Audit und Installationsbereitschaft auf einen Blick
Diese Werte kombinieren öffentliche Repository-Metadaten, OpenAgentSkill-Reviewsignale, Wartungsaktualität und Installationsbereitschaft. Sie helfen bei der Vorauswahl, ersetzen aber keine menschliche Prüfung.
Qualität
VielversprechendUseful candidate, but compare it with alternatives before adopting.
Vertrauen
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Prüfung nötigMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Menschliche Prüfung vor Installation
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
16 GitHub-Stars
Repository-Aktivität
16 Stars und 3 Forks
Wartung
Heute gepusht
Lizenz
Apache-2.0
Installieren
npx skills add danicat/skills --skill swarm-coding
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
shell or command execution, filesystem or document access
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Usable metadata, review docs
Risikoübersicht
Vor Produktion prüfen
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
Installationsbereitschaft
Installationspfad verfügbar
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Lizenz ist angegeben
- Noch keine Agent-Proven-Ergebnisbelege
Agent-lesbare Metadaten
Maschinenlesbare Entscheidungsdaten für diesen Skill.
Nutze diesen Block oder das eingebettete JSON, um zu entscheiden, ob ein Agent diesen Skill installieren, eine Alternative wählen oder zuerst menschliche Prüfung anfordern soll.
Geeignete Aufgaben
- Testing and QA-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
- Run test suites
Geeignete Agents
Installationsentscheidung
- Befehl
- npx skills add danicat/skills --skill swarm-coding
- Richtlinie
- Prüfen
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 53/100
- Audit
- 71/100
- Risikoebene
- Prüfung nötig
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add danicat/skills --skill swarm-codingNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- production agents without a repository review
- Low GitHub adoption signal
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- No OpenAgentSkill engagement data yet
Alternative
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
Alternative
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent-Sicherheit v2
39/100 · Automatische Installation vermeiden
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Hoch
Shell- oder Befehlsausführung
Die Skill-Metadaten verweisen auf Terminal-, CLI-, Shell-, Subprozess- oder Befehlsausführungs-Workflows.
Mittel
Netzwerkzugriff
Die Skill ruft wahrscheinlich Remote-Seiten, APIs, Repositories oder externe Dienste ab.
Mittel
Dateisystemzugriff
Die Skill kann Projektdateien, Dokumente, generierte Artefakte oder den lokalen Arbeitsbereich lesen oder schreiben.
Mittel
Datenbankzugriff
Die Skill kann Schemata prüfen, Datenbanken abfragen oder mit persistenten Speichern arbeiten.
- Hinweise auf Hochrisiko-Berechtigungen: Shell- oder Befehlsausführung
- Dependency or permission surface needs review
Installationsziele
Diesen Skill im Agent-Workflow installieren
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install danicat-swarm-codingAgent-Auflösungsplan
Lass einen Agent die Eignung vor der Installation prüfen.
Die Resolve API liefert die beste Skill, Alternativen, Sicherheitsrichtlinien, Auditnotizen, Installationsziel und einen direkt nutzbaren Prompt.
JSON öffnen
/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve-Text
/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Installationsübergabe
/api/skills/danicat-swarm-coding/install
Agent sollte prüfen
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Prompt kopieren
Task: Use swarm-coding in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/danicat-swarm-coding/install
Install command: npx skills add danicat/skills --skill swarm-coding
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent-Übergabe
Gib dem Agent den Installationspfad, nicht noch ein Verzeichnis.
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
Installationsübergabe
/api/skills/danicat-swarm-coding/install
LLM-Textformat
/api/skills/danicat-swarm-coding/install?format=text
Alternativen finden
/api/skills/search?q=swarm-coding&limit=3
Agent-Prompt
Use swarm-coding for this task. Review https://www.openagentskill.com/api/skills/danicat-swarm-coding/install, then install with: npx skills add danicat/skills --skill swarm-codingRegistry-Metadaten
Agent-lesbares Profil für die automatische Skill-Auswahl.
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Manifest
/api/registry/manifest/danicat-swarm-coding
LLM-Text
/api/registry/manifest/danicat-swarm-coding?format=text
Installationsalias
/api/registry/install/danicat-swarm-coding
Empfehlen
/api/registry/recommend?task=Use%20swarm-coding%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Testing and QA
Plattformen
Claude Code
Audit-Bericht
Prüfung nötig · 71/100
Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
Agent-Entscheidungspanel
Fallback candidate for Testing and QA
Prototype with this skill first; keep a fallback candidate ready.
Rolle im Stack
Fallback-Kandidat
Primäre Eignung
Testing and QA
Vertrauenslabel
Zuerst prototypisieren
Installationspfad
Befehl bereit
Verwenden wenn
- Testing and QA-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
Evidenz
- recent repository activity
- install command or GitHub repo available
- Qualitätsprofil 59/100
zuerst prüfen
- Low GitHub adoption signal
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- No OpenAgentSkill engagement data yet
Implementierungspfad
- 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Testing and QA-Aufgabe vollständig aus.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Vertrauensprofil
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub-Akzeptanz
Beheben16 GitHub-Stars
Star-/Fork-Aktivität
Beheben16 Stars und 3 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
BestandenHeute gepusht
Lizenzklarheit
BestandenApache-2.0
Positive Signale
- KI-Prüfung genehmigt
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Kürzlich gewartetes Repository
- Der Installationsbefehl weist kein offensichtliches Hochrisikomuster auf
- Ergebniszyklus ist bereit, benötigt aber den ersten echten Agent-Lauf
Vor Installation prüfen
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 16 GitHub stars
- Stars/forks activity: 16 stars, 3 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, network or browser surface
- Permission surface: shell or command execution, filesystem or document access
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Choose a stronger alternative or inspect the source manually before any install attempt.
Qualitätsprofil
Vielversprechend Kandidat für Agent-Workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow-Eignung
Diese Skill in diesen Szenarien nutzen
Verify behavior
Testing and QA
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Workflow-Eignung
Zum vollständigen Workflow hinzufügen
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternativen-Shortlist
Vor Installation vergleichen
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Übersicht
--- name: swarm-coding description: > Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for complex, multi-system, or orthogonal engineering initiatives (e.g., concurrent backend, frontend, database, QA). Manages hierarchical Lead Agents and Specialists, disjoint work allocations, and strict parent-child communication. Activate whenever the user mentions 'swarm', requests multi-agent team coordination, or needs context isolation across multiple technical domains. license: Apache-2.0 metadata: category: agents tags: "swarm, subagents, parallel, orchestration, strategy, complexity, coordination" author: Daniela Petruzalek (daniela@danicat.dev) version: "0.2.0" catalog: https://skills.danicat.dev ---
# Swarm Coding
Swarm Coding divides complex engineering objectives among multiple specialized subagents structured in a clear hierarchical organization chart. This divide-and-conquer strategy guarantees context isolation, prevents cross-domain pollution, and accelerates execution by keeping subagent tasks narrowly scoped.
> [!NOTE] > In this guide, the terms "agent" and "subagent" are used interchangeably.
---
## ⚡ Core Principles & Operational Rules
1. **Mandatory Activation:** Activate this skill immediately on any mention of the word "swarm" (case-insensitive) in relation to planning or executing a task. 2. **Coordinator Persistence & Non-Execution:** - The ROOT Swarm Coordinator ALWAYS remains a coordinator and NEVER falls back to an executor. - The Swarm Coordinator is strictly forbidden from writing production implementation code, running tests/builds, or performing direct command execution. 3. **Split Coordinator Profiles:** - **Swarm Coordinator (ROOT):** Attributed strictly to the ROOT agent that activated the skill (Multiplicity: 1). Defines the top-level **Org Chart**, names Lead Agents, allocates the agent budget, writes top-level architecture specs, and coordinates overall progress. - **Lead Agent:** Attributed to domain or system leads (Multiplicity: N, one per system/domain). Receives an allocated sub-budget from the Swarm Coordinator, assembles a specialist team, writes domain specifications, delegates tasks, and integrates domain deliverables. 4. **Specialist Role:** Attributed to task executors. Designs and implements narrowly-scoped components within a single domain, adhering to domain specs and running operational validation loops. 5. **Strict Communication Hierarchy (No Lateral Messaging):** - **Allowed:** Messaging between immediate parents and children ONLY (Swarm Coordinator $\leftrightarrow$ Lead Agent, Lead Agent $\leftrightarrow$ Specialist). - **Forbidden:** Direct communication between agents on the SAME layer (Lead Agent $\leftrightarrow$ Lead Agent, Specialist $\leftrightarrow$ Specialist) or direct escalation (Specialist $\leftrightarrow$ Swarm Coordinator) is strictly forbidden. - **Design Document First:** Inter-domain or cross-layer coordination MUST be handled by writing or updating shared design documents first, then notifying parent/child agents via hierarchical messaging. 6. **Team Continuity & Semi-Permanent Hierarchy (No Disposable Assets):** Treat agents as persistent team members, not disposable assets. Do not prematurely terminate subagents and spawn new ones. Retain and aggressively reuse active Lead Agents and Specialists across task iterations to preserve accumulated context. 7. **Fine-Grained Targeted Testing (No Broad Root Sweeps):** Specialists MUST execute fine-grained, package-scoped unit tests (e.g., `go test ./internal/physics/...`) strictly targeting their assigned task. Running broad project-root test commands (e.g., `go test ./...`) is strictly forbidden for Specialists unless explicitly requested by the Swarm Coordinator, preventing cross-task contamination and false failures while parallel agents work concurrently.
---
## 🎯 Agent Budget & Degree of Parallelism (DOP)
* **Definition**: **Agent Budget** is synonymous with **Degree of Parallelism (DOP)**. It defines the maximum number of **active, concurrent subagents** allowed to execute at the exact same time across the entire swarm hierarchy. * **Active vs. Past Capacity**: Completed or terminated subagents do **not** consume budget. The budget applies strictly to currently running subagents. When a subagent completes its work, its concurrency slot is immediately freed. * **Default Concurrency**: Assumes a default budget of **10** active concurrent agents if omitted by the user. * **Low Budget Guard ($\le 1$):** If the user explicitly specifies an `agent budget <= 1`: - **HALT immediately** and do NOT spawn subagents or start implementation. - Trigger an interactive conversation with the user using `ask_question`. - Explain that multi-agent swarm orchestration requires budget $> 1$ (recommended 10). Present choices: (1) Increase budget to 10 (Recommended), (2) Specify a custom budget $> 1$, or (3) Fall back to single-agent execution. * **Adaptive Team Hierarchy**: - **Focused ($\text{DOP} \le 4$)**: Flat structure (Coordinator $\rightarrow$ Specialists directly). - **Standard / Multi-Domain ($\text{DOP} \ge 6$)**: Hierarchical structure (Coordinator $\rightarrow$ Domain Tech Leads $\rightarrow$ Specialists). - **Massive Swarms ($\text{DOP} \ge 20\text{--}50+$)**: Subagents act as focused micro-probes, returning dense, high-signal structured findings ($\le 150$ words) to enable crisp synthesis without context dilution.
### Concurrency Sizing Matrix:
| Initiative Scale | Agent Budget ($\text{DOP}$) | Structure Type | Domain Tech Leads | Specialists per Lead | Typical Scope | | :--- | :---: | :---: | :---: | :---: | :--- | | **Focused** | **2–4** | Flat | None (Direct Coordinator) | 2–4 Specialists | Targeted dual-subsystem or focused feature | | **Standard (Default)** | **10** | Hierarchical | 2–3 (e.g., Backend, Frontend, QA) | 2–3 per domain | Full-stack application, multi-package service | | **Complex Platform** | **16–20+** | Hierarchical | 4–5 (API, Core Engine, UI, Infra, QA) | 3–4 per domain | Distributed microservices, full platform build | | **Massive Swarm** | **20–50+** | Elastic Micro-Probes | Distributed Leads / Probes | Micro-probes ($\le 150$w) | Wide ecosystem sweeps, multi-file migrations |
---
## 📡 Non-Blocking Coordinator & Reactive Concurrency
The Swarm Coordinator is the primary user interface and top-level organizational conductor. It must remain **unblocked $\ge 99\%$ of the time** to receive steering comments, scope modifications, and status requests from the user.
1. **Role Separation (Delegation over Execution):** - The Swarm Coordinator acts like an engineering director: it breaks down epics, writes top-level architectural contracts, and manages the org chart. It **never** blocks itself with sequential coding, manual building, or terminal test runs. 2. **Fire-and-Yield Concurrency:** - When the Coordinator spawns Lead Agents via `invoke_subagent`, it **immediately halts tool calls to end its turn**. It never loops, sleeps, or polls. 3. **Always Unblocked for User Steering & Status Inquiries:** - Because the Coordinator never enters busy-wait polling loops, it is permanently available to process incoming user messages while the swarm works in the background: - **Status Inquiries**: The Coordinator can immediately provide live progress updates or inspect active workers via `manage_subagents (Action="list")`. - **In-Flight Steering / Scope Changes**: If the user provides new constraints or changes requirements mid-run, the Coordinator can steer active Lead Agents via `send_message` or cancel/restart them via `manage_subagents (Action="kill")`. 4. **Sole User Escalation Interface:** - Subagents do not possess `ask_question`. All requirement ambiguities or design trade-offs encountered by Specialists are messaged up to their Tech Lead, who routes them to the Swarm Coordinator via `send_message`. The Coordinator prompts the user with `ask_question` and relays decisions back down the hierarchy.
---
## 🔄 Map-Reduce Workflow & The "Reduce" (Reconciliation) Step
Swarm Coding operates as a two-stage **Map-Reduce** engineering pipeline:
```mermaid graph TD subgraph Map Phase [1. Map Phase: Parallel Stream Execution] direction TB L1[Tech Lead Backend] --> S1[Specialist: Core API] L1 --> S2[Specialist: Database Models] L2[Tech Lead Frontend] --> S3[Specialist: UI Components] end
subgraph Reduce Phase [2. Reduce Phase: Reconciliation & Final Verification] direction TB AUD[Audit Boundaries & Scan Placeholders] --> WIRE[Task QA/Integration Specialist to Wire Real Components] WIRE --> PURGE[Purge Temporary Stubs & Mock Adapters] PURGE --> E2E[Run End-to-End Integration Test Suite] E2E --> PROOF[Deliver Verified Evidence Log to Coordinator] end
Map Phase --> Reduce Phase ```
### 1. Map Phase (Parallel Development & Collision Avoidance) * **Flexible Subagent Prompting**: Provide clear domain goals and target boundaries in prompts without brittle syntax constraints. * **Tech Lead Arbitration**: Team Leads dynamically arbitrate file boundaries and dependencies among their specialists as changes evolve. * **Temporary Interface Contracts**: When Specialist A depends on in-progress work from Specialist B, they program against agreed interface stubs or mocks.
### 2. The Final "Reduce" Phase (Integration & Placeholder Purge) Parallel execution often leaves behind temporary mocks or stubs where real implementations were created by peer agents. Before declaring success, the Coordinator orchestrates the final **Reduce** step:
1. **Placeholder & Stub Audit**: Scans code boundaries to ensure no dangling `TODO` comments, dummy return values, or temporary mock adapters survive. 2. **Reconciliation & Real Component Wiring**: The Coordinator tasks a designated **Integration/QA Specialist** to connect all real modules together. 3. **End-to-End Project Verification**: The QA Specialist runs full project builds, integration tests, and linters, reporting actual terminal proof back to the Coordinator before final delivery to the user.
---
## 👥 Mechanics and Roles
Subagents in a Swarm Coding session assume one of three roles:
1. **Swarm Coordinator (ROOT)** [Multiplicity: 1] - Acts as top-level architect and organizational manager. - Defines the **Org Chart**, names Lead Agents for each domain, allocates agent budgets, and writes top-level architecture specs. - **Persistence & Non-Execution:** Strictly forbidden from executing code or running build/test commands. - **Sole User Interface:** Sole agent in the swarm authorized to interact with the user via `ask_question`. 2. **Lead Agent (Domain Tech Lead)** [Multiplicity: N] - Technical lead for a specific domain or system (e.g., Frontend, Backend, Database). - Assembles a Specialist team within their allocated sub-budget, writes domain specs ("Design Document First"), deconstructs domain tasks, arbitrates collisions, and integrates deliverables. - **Tool Restrictions:** Command/script execution is disabled (`commandExecutionPolicy: off`). Delegates execution to Specialists and routes user questions up to the Swarm Coordinator via `send_message`. 3. **Specialist (Task Implementer / QA)** [Multiplicity: N] - Executes narrowly-scoped technical tasks within their assigned domain. - Follows domain specifications, executes the operational validation loop (build, test, lint, format), replaces stubs, and provides proof-of-validation logs to their parent Lead Agent.
---
## 💬 Communication Hierarchy & Rules
```mermaid graph TD ROOT["Swarm Coordinator (ROOT)"] <-->|Parent-Child Message| LEAD1["Lead Agent (Backend)"] ROOT <-->|Parent-Child Message| LEAD2["Lead Agent (Frontend)"] LEAD1 <-->|Parent-Child Message| SPEC1["Specialist (API Dev)"] LEAD1 <-->|Parent-Child Messa
Technische Details
- Version
- 1.0.0
- Lizenz
- Apache-2.0
- Letzte Aktualisierung
- 24. Aug. 2026
- Veröffentlicht
- 24. Aug. 2026
Entscheidungsübersicht
Fallback-Kandidat
recent repository activity
Audit
Installationsprüfung
Installations- und Adoptionsprüfung
- Sicherheit
- 72/100
- Wartung
- 100/100
- Installieren
- 92/100
Von Agent belegte Evidenz
Von Agent belegte Evidenz
Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.
- Erfolgsrate
- —
- Letzter Fehler
- —
- Ergebnisse
- 0
- Ausgabequalität
- —
- Fehlgeschlagen
- 0
- Nicht relevant
- 0
- Installationen
- 0
- Durch Risiko blockiert
- 0
- Einrichtung erforderlich
- 0
- Produktion
- 0
Noch keine Agent-Ergebnisdaten. Der erste Lauf kann Erfolg, Einrichtungsbedarf, Risikoblockaden, Fehler oder Irrelevanz über /api/agent/outcome melden.
Installieren
Zum Agent-Workflow hinzufügen
Kostenlos und Open Source. Bericht vor der Installation in Produktions-Agents prüfen.
Wachstums-Loop
Share-Kit
Szenariobasierter Entwurf für swarm-coding, bereit für einen manuellen X-Post.
swarm-coding: Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for comp... 16 stars https://www.openagentskill.com/skills/danicat-swarm-coding?ref=x
Optionale Antwort mit Installationsbefehl
Listing + install path for swarm-coding: https://www.openagentskill.com/skills/danicat-swarm-coding?ref=x Install: npx skills add danicat/skills --skill swarm-coding
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- danicat
- Quelle
- danicat/skills
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird danicat zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](https://www.openagentskill.com/skills/danicat-swarm-coding)
[](https://www.openagentskill.com/skills/danicat-swarm-coding)
[](https://www.openagentskill.com/skills/danicat-swarm-coding/audit)
[](https://www.openagentskill.com/skills/danicat-swarm-coding)Autor
danicat
@danicat
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 16
- Qualitätswert
- 32/100
- Letzter GitHub-Push
- 23. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 0
- Installationskopien
- 0
- Externe Klicks
- 0
Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
Vertrauen & Sicherheit
Do not auto-install
- GitHub-Akzeptanz16 GitHub-StarsBeheben
- Star-/Fork-Aktivität16 Stars und 3 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarBeheben
- Aktuelle WartungHeute gepushtBestanden
- LizenzklarheitApache-2.0Bestanden
- README/SKILL.md-VollständigkeitÖffentliche Metadaten benötigen mehr README/SKILL.md-KontextInfo
- Abhängigkeits-/Laufzeitrisikocommand execution surface, network or browser surfacePrüfen
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