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 instructions/hltcoe/routir/claude-mdgit clone --depth 1 https://github.com/hltcoe/routirWrote 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/instructions/hltcoe/routir/claude-md)<a href="https://agentmods.dev/instructions/hltcoe/routir/claude-md"><img src="https://agentmods.dev/badge/instructions/hltcoe/routir/claude-md.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 | $0.04146 | $0.04146 |
| Opus 5 | $0.02073 | $0.02073 |
| Sonnet 5 | $0.00829 | $0.00829 |
| Haiku 4.5 | $0.00415 | $0.00415 |
Grade A, and why
routir CLAUDE.md scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Smoke-test a reranker (`curl` is not Python, so it runs directly): How it starts
The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RoutIR — src/routir
RoutIR is an async search/retrieval service. It hosts retrieval models (dense, sparse, rerankers, fusion, query expanders) behind a uniform HTTP/gRPC API and lets you compose them into multi-stage pipelines with a small DSL. This file orients an agent who needs to add a new engine (a reranker, search engine, query expander, or fusion method).
For task-oriented walkthroughs — calling the client, standing up a local server that
imports a master server, wrapping a bi-encoder or reranker via file_imports, and
serving multi-view collections — see SKILL.md.
The one concept that matters: Engine
Everything pluggable is a subclass of Engine (src/routir/models/abstract.py). An engine
declares its capabilities simply by which methods it overrides — there is no registration
boilerplate, no capability flag to set. The base class auto-detects capabilities by checking
whether you overrode the *_batch method:
| Override this method | Capability (can_*) |
Pipeline role | Service type registered |
|---|---|---|---|
search_batch |
can_search |
search |
search |
score_batch |
can_score |
rerank |
score |
decompose_query_batch |
can_decompose_query |
expander |
decompose_query |
fuse_batch |
can_fuse |
merger |
fuse |
(The role→service-type map lives in src/routir/pipeline/pipeline.py as _role_to_service.)
A single engine may implement several of these. SentenceTransformerEngine implements both
search_batch and score_batch, for example. Implement only the methods that apply; the
rest raise NotImplementedError and the capability stays off.
*_batch is always the method to override. The singular convenience wrappers
(search, score, decompose_query, fuse) just call the batch form with one item — don't
override them. The exception is legacy code like MT5Reranker, which overrode score; prefer
score_batch in new engines.
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 · 294 lines · 4,146 tokens per session scan A aa4b38e9bcc7
routir CLAUDE.md is an instructions file published in the GitHub repository hltcoe/routir (14 stars, last pushed 3mo ago), licensed MIT. It adds 4,146 tokens to every session, about $0.0207 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other instructions, from other repositories
GPT-RAG release.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.
ken CLAUDE.md
Claude Code instructions for townsendmerino/ken, covering claude.md, what this is, repository ownership (read this first), commands and embedding parity & golden fixtures (now in aikit).
rag-code-mcp copilot-instructions.md
Instructions for doITmagic/rag-code-mcp, covering copilot instructions - ragcode mcp, ⚖️ the golden rule, project overview, architecture & patterns and developer workflows.
ZipAI CLAUDE.md
Claude Code instructions for nickdesi/ZipAI, covering claude.md — zipai: ultra-dense token optimizer, rules, 1. zero filler, 2. ambiguity and 3. prompt caching.
gpu-ai-skills CLAUDE.md
Claude Code instructions for intel/gpu-ai-skills, covering claude.md, what this repository is, repository structure, commands and validation (required before any skill change).
TreeSkill CLAUDE.md
Instructions for JimmyMa99/TreeSkill, covering claude.md, project overview, commands, install and run tests.