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 AnthonyAlcaraz/agentic-graph-rag-skills --skill hierarchical-orchestration-routergit clone --depth 1 https://github.com/AnthonyAlcaraz/agentic-graph-rag-skillsWrote 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/anthonyalcaraz/agentic-graph-rag-skills/hierarchical-orchestration-router)<a href="https://agentmods.dev/skills/anthonyalcaraz/agentic-graph-rag-skills/hierarchical-orchestration-router"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/hierarchical-orchestration-router/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/anthonyalcaraz/agentic-graph-rag-skills/hierarchical-orchestration-router"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/hierarchical-orchestration-router.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 | $0.00183 | $0.02360 |
| Opus 5 | $0.00092 | $0.01180 |
| Sonnet 5 | $0.00037 | $0.00472 |
| Haiku 4.5 | $0.00018 | $0.00236 |
Grade A, and why
hierarchical-orchestration-router 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 12d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hierarchical Orchestration Router
Overview
Discovery and retrieval find the right tool. Orchestration coordinates them at scale. As tool counts grow from dozens to hundreds and agent counts from one to many, you need infrastructure that routes requests, manages failover, and enforces governance. This skill composes three ideas from the chapter's "Orchestration at Scale" section.
Inversion — one orchestrator, not thousands of tools. Instead of exposing every tool to the agent, expose exactly one: an intelligent orchestrator that handles all complexity. The agent asks for an outcome; the orchestrator decides how to achieve it. This is what lets traditional SaaS answer "why did we lose deals last quarter?" in seconds instead of through menus and reports.
Hierarchical routing. Organizations don't just have more tools — they have multiple MCP servers across departments (Sales, Finance, Operations), each managing hundreds of tools. The router classifies a query into a domain by semantics. High confidence (> 0.8) routes to that domain's orchestrator; low confidence means the query spans domains, so it invokes cross-domain orchestration (chapter Example 6-11). This buys fault isolation (a logistics outage does not stop sales), scalable governance (global vs domain-local policies), and progressive disclosure (users see only capabilities relevant to their context).
Functional clustering for resilience. Within a domain, tools with similar function are clustered for intelligent failover. Baidu's AI Search Paradigm embeds tools by what they DO (DRAFT-refined docs + usage patterns), then K-means++ groups them into functional toolkits. When the primary tool is overloaded, the orchestrator fails over to a functionally-equivalent alternative from the same cluster — a "Search Toolkit" of Baidu AI Search / ArXiv MCP / Perplexity / OpenAI WebSearch — adapting parameters as it fails over. No single point of failure.
When to Use
- Multiple departments/domains each own many tools (or MCP servers)
- Queries arrive that may belong to one domain or span several
- You need failover: when one tool is overloaded, route to an equivalent
- You are turning a legacy multi-tool surface into a single natural-language entry
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 177 lines · 183 tokens per session scan A 035ec20cc2d4
hierarchical-orchestration-router is a skill published in the GitHub repository AnthonyAlcaraz/agentic-graph-rag-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 183 tokens to every session and 2,360 once invoked, about $0.0009 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.
Other skills, from other repositories
graphify
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community…
lemmalog
Externalize working memory and logical state into the lemmalog Datalog engine (MCP). Use for ANY multi-step task where state should outlive one context window or span agents: long investigations, debugging sessions, audits, multi-agent searches, systematic explorations, planning with many interdependent constraints…
jurisd-research
Expert Australian/NZ legal research and AGLC4 citation using the jurisd MCP server. Use when finding cases or legislation (AustLII), looking up a provision offline, formatting or resolving citations, building a pinpoint, tracing who-cites-what, or producing an AGLC4 bibliography. Triggers on case law, legislation…
repo_search
Search repository text through a deterministic first-class fak command.
container-manager-kg-ingestion
Snapshot a host's Docker/Podman/Swarm inventory into the epistemic-graph knowledge graph as typed OWL nodes via the container-manager-mcp MCP server — containers, images, volumes, networks, swarm services and nodes, with their :usesImage / :runsOn / :builtFrom links. Use when the agent must record live container state…
cortex-design
Use this skill to generate well-branded interfaces and assets for Cortex, either for production or throwaway prototypes/mocks/etc. Contains essential design guidelines, colors, type, fonts, assets, and UI kit components for prototyping.