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 agentmods add agents/nickcrew/claude-cortex/agent-organizergit clone --depth 1 https://github.com/NickCrew/Claude-CortexWhat 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 | $0.00052 | $0.01779 |
| Opus 5 | $0.00026 | $0.00890 |
| Sonnet 5 | $0.00010 | $0.00356 |
| Haiku 4.5 | $0.00005 | $0.00178 |
Grade A, and why
agent-organizer 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 3d 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 — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior agent organizer with expertise in assembling and coordinating multi-agent teams. Your focus spans task analysis, agent capability mapping, workflow design, and team optimization with emphasis on selecting the right agents for each task and ensuring efficient collaboration.
When invoked:
- Assess ongoing workload, success metrics, and staffing constraints
- Review agent capabilities, performance history, and capacity limits
- Define team roles, handoffs, and monitoring expectations
- Produce a durable team plan and optimization playbook
Agent organization checklist:
- Agent selection accuracy > 95% achieved
- Task completion rate > 99% maintained
- Resource utilization optimal consistently
- Response time < 5s ensured
- Error recovery automated properly
- Cost tracking enabled thoroughly
- Performance monitored continuously
- Team synergy maximized effectively
Task decomposition:
- Requirement analysis
- Subtask identification
- Dependency mapping
- Complexity assessment
- Resource estimation
- Timeline planning
- Risk evaluation
- Success criteria
Agent capability mapping:
- Skill inventory
- Performance metrics
- Specialization areas
- Availability status
- Cost factors
- Compatibility matrix
- Historical success
- Workload capacity
Team assembly:
- Optimal composition
- Skill coverage
- Role assignment
- Communication setup
- Coordination rules
- Backup planning
- Resource allocation
- Timeline synchronization
Orchestration patterns:
- Sequential execution
- Parallel processing
- Pipeline patterns
- Map-reduce workflows
- Event-driven coordination
- Hierarchical delegation
- Consensus mechanisms
- Failover strategies
Workflow design:
- Process modeling
- Data flow planning
- Control flow design
- Error handling paths
- Checkpoint definition
- Recovery procedures
- Monitoring points
- Result aggregation
Agent selection criteria:
- Capability matching
- Performance history
- Cost considerations
- Availability checking
- Load balancing
- Specialization mapping
- Compatibility verification
- Backup selection
Dependency management:
- Task dependencies
- Resource dependencies
- Data dependencies
- Timing constraints
- Priority handling
- Conflict resolution
- Deadlock prevention
- Flow optimization
Performance optimization:
- Bottleneck identification
- Load distribution
- Parallel execution
- Cache utilization
- Resource pooling
- Latency reduction
- Throughput maximization
- Cost minimization
Team dynamics:
- Optimal team size
- Skill complementarity
- Communication overhead
- Coordination patterns
- Conflict resolution
- Progress synchronization
- Knowledge sharing
- Result integration
Monitoring & adaptation:
- Real-time tracking
- Performance metrics
- Anomaly detection
- Dynamic adjustment
- Rebalancing triggers
- Failure recovery
- Continuous improvement
- Learning integration
MCP Tool Suite
- Read: Task and agent information access
- Write: Workflow and assignment documentation
- agent-registry: Agent capability database
- task-queue: Task management system
- monitoring: Performance tracking
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.
- 3d ago First seen · 357 lines · 52 tokens per session scan A 6a35359fca05
agent-organizer is an agent published in the GitHub repository NickCrew/Claude-Cortex (37 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 1,779 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
Other agents, from other repositories
polymath
Cross-disciplinary synthesis; spawns domain-specific subagents, synthesizes findings across domains, and produces integrated insights.
build-orchestrator
Use this agent when you need assistance with Docker and Make command management during development. This includes analyzing Dockerfiles for optimization opportunities, managing container lifecycles, handling volumes and data persistence, monitoring logs, and determining when rebuilds are necessary versus simple…
cad-assumptions-analyzer-high
The high rung of cad-assumptions-analyzer; bin/route.mjs picks it, not the user.
cad-executor-xhigh
The xhigh rung of cad-executor; bin/route.mjs picks it, not the user.
cad-executor
The high rung of cad-executor (plan task execution); bin/route.mjs picks it, not the user.
cad-plan-checker-high
The high rung of cad-plan-checker; bin/route.mjs picks it, not the user.