Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add varunk130/ai-workflow-playbooks --skill multi-agent-collaborationgit clone --depth 1 https://github.com/varunk130/ai-workflow-playbooksWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/multi-agent-collaboration)<a href="https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/multi-agent-collaboration"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/multi-agent-collaboration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/multi-agent-collaboration"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/multi-agent-collaboration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.00681 |
| Opus 5.5 | $0.00008 | $0.00272 |
| Sonnet 5.5 | $0.00004 | $0.00136 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
multi-agent-collaboration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Collaboration
What This Skill Enables
An agent that can operate alongside other agents - dividing work, avoiding conflicts, and maintaining consistency - without stepping on each other's changes or duplicating effort. Without this skill, multi-agent workflows produce merge conflicts, inconsistent patterns, and wasted cycles.
Core Competencies
1. Work Partitioning
Divide tasks so agents work on independent surfaces:
- By file: Agent A owns
auth/, Agent B ownsdashboard/ - By layer: Agent A handles API endpoints, Agent B handles UI components
- By feature slice: Agent A builds user creation end-to-end, Agent B builds search end-to-end
- Never: Two agents modifying the same file simultaneously
2. Contract Agreement
When agents produce code that connects, define the contract first:
- Agree on interface signatures (function names, parameter types, return types)
- Agree on data shapes (request/response schemas, event payloads)
- Write the interface or type definition first, implement second
- Both agents can work in parallel once the contract is locked
3. Convention Adherence
Multiple agents must produce code that looks like one person wrote it:
- Read the project's style guide or infer it from existing code before writing
- Use the same naming patterns, file structure, and error handling approach
- Run the same linter and formatter configuration
- Follow the same commit message format
4. Conflict Prevention
Avoid merge conflicts proactively:
- Check which files other agents have modified before starting
- Prefer additive changes (new files) over modifications to shared files
- When shared files must change, coordinate the order - one agent goes first
- Use feature flags to integrate work independently
5. Handoff Protocol
When passing work to another agent:
HANDOFF NOTE:
- What I completed: [list of files/features implemented]
- What I tested: [which tests pass, what was verified]
- What remains: [tasks not yet started]
- Assumptions I made: [decisions the next agent should know about]
- Known issues: [anything broken or incomplete]
- Files to read first: [most important context files]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 69 lines · 21 tokens per session scan A 89e93e9be576
multi-agent-collaboration is a skill published in the GitHub repository varunk130/ai-workflow-playbooks (2 stars, last pushed 24d ago), licensed MIT. It adds 21 tokens to every session and 681 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
customer-journey-map
Construye un mapa de recorrido del cliente para un producto, servicio o experiencia. Úsalo cuando se te pida mapear un recorrido del cliente, crear un viaje del usuario, documentar puntos de contacto y puntos de fricción, o diseñar un mapa de experiencia. Produce un mapa de recorrido completo con etapas, puntos de…
user-story-writer
Escribir historias de usuario bien estructuradas con criterios de aceptación y casos extremos. Úsalo cuando te pidan escribir historias de usuario, crear tickets a partir de un resumen de características, convertir un PRD en historias o redactar criterios de aceptación. Produce historias listas para estimar en formato…
feature-prioritisation
Aplica marcos de priorización (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) para clasificar características e items del backlog. Úsalo cuando se te pida priorizar características, clasificar un backlog, decidir qué construir a continuación, o evaluar compensaciones entre ideas competidoras. Produce una lista de…
morning-intelligence
Interviews you across 15 questions to capture your role, topics, sources, exclusions, and format preferences, then writes a master prompt you can paste into a scheduled task or Claude Code Routine. Use when you want to set up a personalised daily news brief, build a reusable morning news prompt, or create an automated…
data-analysis-standard
Estructura un análisis de datos de producto, análisis profundo de métricas, análisis de embudo o estudio de cohortes. Úsalo cuando te pidan analizar métricas de producto, investigar una caída en conversión, explicar un cambio de datos a stakeholders o encontrar la causa raíz de un movimiento de métrica. Produce un…
technical-spec-template
Crea documentos de especificación técnica estructurados que conectan requisitos de producto con implementación de ingeniería. Úsalo cuando escribas una especificación técnica, especificación de ingeniería, documento de diseño de sistema o especificación de API. Produce una especificación completa con declaración del…