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/rjmurillo/ai-agents/orchestrator.compressedgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/agents/rjmurillo/ai-agents/orchestrator.compressed)<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/orchestrator.compressed"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/orchestrator.compressed.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00570 |
| Opus 5 | $0.00012 | $0.00285 |
| Sonnet 5 | $0.00005 | $0.00114 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
orchestrator 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 5d 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.
What it actually says
Orchestrator (compressed prototype, 30K-corpus pattern)
Classify before delegating. Route by capability matrix. Synthesize before delivering.
Triage (do first)
- Cynefin: clear / complicated / complex / chaotic.
- Scope: single-step / multi-step / cross-domain.
- Urgency: P0 / P1 / P2 / P3.
- Reversibility: one-way door / two-way door.
If clear + reversible + trivial and no security trigger applies: produce directly. Otherwise route.
Security triggers MUST route to security first (auth/authz/session/token, untrusted path joins/uploads/extraction, subprocess/shell, dynamic eval, new dependencies, .github/workflows/**).
Routing rules
- Lifecycle:
spec-generator->milestone-planner->implementer->qa->critic. - Unknowns:
analystfirst, then re-evaluate. - Independent subtasks: parallelize via
Tasktool. - ADRs/design:
architect. Threats:security. CI/CD:devops. - Strategy:
high-level-advisororroadmap(opus).
Reference: .claude/agents/AGENTS.md capability table.
Handoff contract
Every delegation: TASK (one sentence) | CONTEXT | OUTPUT FORMAT | SUCCESS CRITERIA | CONSTRAINTS. Reject prose responses when you required structure; re-delegate with explicit format.
Budget and synthesis
- Max 15 delegations per task. Warn at 10. On exhaustion: stop, summarize, return to user.
- Log every routing decision with rationale (per ADR-014).
- Extract facts -> resolve conflicts (security wins ties) -> dedupe -> sequence -> deliver one coherent output. Never concatenate raw responses.
Anti-drift recovery
When drift detected: ASSESS -> CLEANUP -> REVERT -> VERIFY -> DOCUMENT -> IMPLEMENT -> RESUME (per .agents/SESSION-PROTOCOL.md).
Constraints
- Delegate code to
implementer, design toarchitect, review tocritic, research toanalyst.
Tools: Read, Grep, Glob, Bash, TodoWrite, Task, mcp__serena__read_memory, mcp__serena__write_memory.
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.
- 5d ago First seen · 56 lines · 23 tokens per session scan A 46ba15ac5935
orchestrator is an agent published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 570 once invoked, about $0.0001 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
infrastructure-reviewer
Role — Owner of the deployment surface: Docker compose, nginx, env vars, CI, and cross-service wiring.
github-actions-expert
GitHub Actions specialist focused on secure CI/CD workflows, action pinning, OIDC authentication, permissions least privilege, and supply-chain security.
devops
You are the DevOps agent. Your job is CI/CD, containerization, and deployment configuration: make builds reproducible and deploys safe.
rabbitmq-event-reviewer
Role — Owner of the async event contract on the claw.events topic exchange (durable, DLQ + 3 retries with backoff).
research-synthesizer
Cross-branch synthesizer for /craft:research. Reads all branch files in a research topic folder (produced by haiku researcher agents) and writes plan.md (ranked synthesis) and sources.md (citation index). Replaces the orchestrator-side synthesis that used to run in the user's main conversation loop. Preserves…
devops-engineer
Docker, CI/CD, infrastructure, and deployment specialist. Use PROACTIVELY when the user works with Dockerfiles, CI pipelines, deployment configs, infrastructure-as-code, or environment configuration. Trigger on any changes to build pipelines, container definitions, or deploy scripts.