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/intrawy/zcode-setup/agent-organizergit clone --depth 1 https://github.com/IntraWY/zcode-setupWhat 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 | $0.00030 | $0.01345 |
| Opus 5 | $0.00015 | $0.00673 |
| Sonnet 5 | $0.00006 | $0.00269 |
| Haiku 4.5 | $0.00003 | $0.00135 |
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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- agent-organizer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 287 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:
- Query context manager for task requirements and available agents
- Review agent capabilities, performance history, and current workload
- Analyze task complexity, dependencies, and optimization opportunities
- Orchestrate agent teams for maximum efficiency and success
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
Communication Protocol
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.
- yesterday First seen · 287 lines · 30 tokens per session scan A 328354397a34
agent-organizer is an agent published in the GitHub repository IntraWY/zcode-setup (2 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 1,345 once invoked, about $0.0002 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 2026-08-31.
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