Agent skill

Run Shunt

by pleaseai in pleaseai/shunt

Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy).

Apache-2.0Auto-check passedTesting & QA

Install Run Shunt

skills CLI
$ npx skills add pleaseai/shunt --skill run-shunt -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pleaseai/shunt run-shunt --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pleaseai/shunt.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/run-shunt .claude/skills/run-shunt && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
run-shunt
GitHub stars
281
Token cost
~2.6k tokens
SKILL.md length
988 words
Files
3
Skills in repo
2
Repo updated
First seen
Licence
Apache-2.0

At a glance

Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy).

  • Curl-drive the gateway
  • SKILL.md covers Prerequisites, Build, Run (agent path) — the smoke… and Direct invocation (internal…, plus 3 more sections
  • Runs Shell scripts from its folder; calls cargo, jq and curl; needs ANTHROPIC_AUTH_TOKEN
  • Exercise /v1/models discovery and /v1/messages proxying

What it does

Run Shunt is an agent skill from pleaseai/shunt. Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy). Use to run, start, smoke-test, or curl-drive the gateway, exercise /v1/models discovery and /v1/messages proxying, or connect Claude Code to a local shunt instance.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `smoke.sh` and `test_smoke.sh`).

It sits in Testing & QA, covering Model routing and gateways and QA and bug reports. It works with Rust, OpenAI, Google Gemini and Kimi. The repository describes itself as: Shunt Claude Code agents to any model — selective, per-agent inference-layer routing proxy. The licence is Apache-2.0.

When your agent uses it

  • Curl-drive the gateway
  • Exercise /v1/models discovery and /v1/messages proxying
  • Connect Claude Code to a local shunt instance

Example prompts

  • “/run-shunt”

Requirements

  • Python 3
  • A Bash shell
  • A credential in ANTHROPIC_AUTH_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit e147f9b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • cargo
    • jq
    • curl
    • python3
    • claude
    • apt-get
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com
    • code.claude.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ANTHROPIC_AUTH_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Run Shunt loads about 2.6k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 988 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pleaseai/shunt at commit e147f9b, republished under its Apache-2.0 licence (© pleaseai). 988 words, ~2,551 tokens.

Download SKILL.mdSave it as .claude/skills/run-shunt/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
run-shunt
description
Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy). Use to run, start, smoke-test, or curl-drive the gateway, exercise /v1/models discovery and /v1/messages proxying, or connect Claude Code to a local shunt instance.

Run shunt

shunt is a Rust (axum) HTTP server — a Claude Code LLM gateway. It has no GUI: you drive it with curl. It listens on 127.0.0.1:3001 by default and serves an Anthropic-Messages surface (GET /v1/models, POST /v1/messages, POST /v1/messages/count_tokens, HEAD /). For each mapped model id it diverts inference to another provider (OpenAI / Codex / ChatGPT via the OpenAI Responses API); everything else passes through to Anthropic.

Primary agent path: run the committed driver .claude/skills/run-shunt/smoke.sh. It builds the binary, spins up a local mock upstream (so no real API key is needed), launches the gateway, and drives every route end to end with assertions. That is the way to confirm a change works.

All paths below are relative to the repo root (the shunt/ directory).

Prerequisites

Everything the driver needs is already standard on macOS/Linux dev boxes:

bash
cargo --version     # Rust stable (built with 1.94); toolchain via rust-toolchain.toml if present
python3 --version   # smoke.sh uses http.server as a stand-in upstream
curl --version
jq --version        # smoke.sh asserts JSON responses with jq
lsof -v

On a bare Ubuntu container: apt-get install -y curl jq lsof python3 and install Rust via rustup if cargo is missing.

Build

bash
BIN="$(cargo build --locked --message-format=json-render-diagnostics | jq -sr '[.[] | select(.reason == "compiler-artifact" and .target.name == "shunt" and (.target.kind | index("bin"))) | .executable | select(. != null)] | last // empty')"
test -x "$BIN"

BIN resolves Cargo's actual executable path, including CARGO_TARGET_DIR and a configured target triple.

Run (agent path) — the smoke driver

This is what you run to see shunt working. It is hermetic (no network, no credentials) and exits non-zero on the first failed assertion.

bash
.claude/skills/run-shunt/smoke.sh

Expected tail:

  PASS shunt check -> config ok
  PASS HEAD / -> 200 (server live)
  PASS GET /v1/models returns configured model
  PASS POST /v1/messages proxied to upstream and returned its body
  PASS malformed request -> 400 invalid_request_error
  PASS GET /health reports ok
  PASS GET /protocol describes the anthropic-messages contract
  PASS GET /routes resolves the configured route
  PASS POST /v1/messages/count_tokens proxied to upstream on its own path
All smoke checks passed.

What it covers: every route the server registers unconditionally. Config validation (shunt check), liveness (HEAD /), health (GET /health), the gateway contract (GET /protocol), model discovery (GET /v1/models), the resolved route table (GET /routes), both proxy forward paths (POST /v1/messages and POST /v1/messages/count_tokens, routed to a local mock that stands in for api.anthropic.com and asserted by the path it forwarded to), and the routing error path (a body with no model field → 400 invalid_request_error). Routes that only an optional config section registers (the Codex endpoint, the usage surfaces) are out of scope, since the smoke config does not enable them.

SHUNT_PORT and MOCK_PORT default to 31711 and 31712. Set either to 0 to bind an ephemeral port instead, which is the conflict-free way to run the driver beside a live gateway.

The driver has its own regression, test_smoke.sh. Run it after editing smoke.sh. It proves the driver refuses a port outside 0..65535 by name; refuses a port another listener already holds, where the real process dies at bind and the driver says which one died; and refuses a shunt listening on a port it never requested, which is the case the pid-derived readiness check catches. It then runs the normal path. The stand-in listener answers every assertion the driver makes, so a driver that trusted $SHUNT_PORT over the process it started would go green against it and get caught.

Drive it by hand

Write a config, launch, and curl it yourself:

bash
BIN="$(cargo build --locked --message-format=json-render-diagnostics | jq -sr '[.[] | select(.reason == "compiler-artifact" and .target.name == "shunt" and (.target.kind | index("bin"))) | .executable | select(. != null)] | last // empty')"
test -x "$BIN"
"$BIN" run --config ./shunt.toml    # or copy shunt.toml.example first

Then, against the running server:

bash
curl -s "http://127.0.0.1:3001/v1/models?limit=1000" | jq .
# => {"data":[{"id":"claude-opus-via-codex","display_name":"Opus (via Codex)"}]}

Validate a config without starting the server:

bash
BIN="$(cargo build --locked --message-format=json-render-diagnostics | jq -sr '[.[] | select(.reason == "compiler-artifact" and .target.name == "shunt" and (.target.kind | index("bin"))) | .executable | select(. != null)] | last // empty')"
test -x "$BIN"
"$BIN" check --config ./shunt.toml   # prints "config ok" or a precise error

CLI shape: shunt run|check [--config <path>] (also shunt --check). Default config path is ./shunt.toml; SHUNT_-prefixed env vars override (with __ for nesting).

Direct invocation (internal logic — most PRs touch this)

The interesting code is the Anthropic Messages ⇄ OpenAI Responses translation (src/adapters/, src/model/) and routing (src/routing.rs). These are covered by unit + integration tests — the fastest inner loop for a PR touching them:

bash
cargo test --workspace                              # all tests
cargo test --test responses_translate               # the translation integration suite

Full pre-PR gate (matches CI):

bash
cargo fmt --all --check
cargo clippy --all-targets --all-features -- -D warnings
cargo test --all-features --workspace

Run (human path) — connect Claude Code to a local shunt

Point Claude Code at the running gateway. shunt does not validate the credential, but Claude Code still needs one set or it drops to its login wizard. Per the gateway-connect docs:

bash
export ANTHROPIC_BASE_URL=http://127.0.0.1:3001
export ANTHROPIC_AUTH_TOKEN=local-dummy        # any string; shunt ignores it
export CLAUDE_CODE_ENABLE_GATEWAY_MODEL_DISCOVERY=1   # opt-in: pull /v1/models into the picker
export ANTHROPIC_CUSTOM_MODEL_OPTION=gpt-5.2-codex    # add a non-claude id to /model (see Gotchas)
claude    # started from the same shell; /status shows the base URL

Verify the wiring without opening Claude Code (this is the docs' own check):

bash
curl -X POST "$ANTHROPIC_BASE_URL/v1/messages" \
  -H "Authorization: Bearer $ANTHROPIC_AUTH_TOKEN" \
  -H "anthropic-version: 2023-06-01" -H "content-type: application/json" \
  -d '{"model":"claude-opus-via-codex","max_tokens":1,"messages":[{"role":"user","content":"."}]}'

With a default (anthropic-routed) config this forwards to api.anthropic.com and needs a real Anthropic key in the header to get a 200; a mapped model routed to openai/codex needs that provider's credential instead. For a credential-free run, use smoke.sh (mock upstream) rather than this path.

Show full SKILL.md (369 more words)Show less

Gotchas

  • No GUI, no npm start. It's a Rust HTTP server. "Running it" means launch + curl. The driver is the smoke script.
  • Model discovery drops non-claude/anthropic ids. Claude Code's /v1/models importer ignores any id not starting with claude or anthropic, so to route to e.g. gpt-5.2-codex you either alias it under a claude… discovery id or add it via ANTHROPIC_CUSTOM_MODEL_OPTION (the primary way). This is a Claude Code constraint, not a shunt bug.
  • shunt ignores the request credential. GET /v1/models reads authorization/x-api-key but discards it (src/discovery.rs), and the proxy just forwards headers upstream. So any dummy token works for local driving — the real key only matters to the upstream provider.
  • shunt check is strict about provider shape. providers.openai.adapter and providers.codex.adapter must be "responses"; openai.auth must be api_key, codex.auth must be chatgpt_oauth — otherwise check fails with a specific error (src/config.rs). Partial TOML is fine: figment merges your file over built-in defaults, so you only need to specify what differs.
  • A discovery [[models]] entry with no matching [[routes]] logs a WARN at startup/check but is not fatal.
  • GET /protocol is the machine-readable gateway contract. It is unauthenticated and reports shunt's package version, Anthropic-Messages format, supported endpoints, header handling, attribution behavior, and model-discovery constraints.
  • zsh quoting: quote URLs containing ? (globbing) and mind noclobber on > redirects when driving by hand in this repo's shell.

Troubleshooting

  • smoke.sh reports shunt exited during startup or mock upstream exited during startup: the dumped log says Address already in use, so a stale process holds that test port. Run lsof -nP -iTCP:${MOCK_PORT:-31712} -sTCP:LISTEN for the mock port or replace it with ${SHUNT_PORT:-31711} for the gateway port. Stop the reported PID, then re-run. SHUNT_PORT=0 MOCK_PORT=0 skips the conflict outright by binding ephemeral ports.
  • 502 Bad Gateway / api_error: error sending request for url (...) — shunt reached routing but the upstream base_url was unreachable (wrong host/port, or the mock/provider isn't up). This is the correct error mapping (src/error.rs), not a crash. Check the target base_url.
  • 400 invalid_request_error: request body must include a JSON model field — the request body isn't JSON with a model key. Routing happens before forwarding (src/routing.rs).
  • cargo clippy fails the build — CI sets RUSTFLAGS=-D warnings; warnings are errors. Fix them before a PR (cargo clippy --all-targets --all-features -- -D warnings).

© pleaseai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in .claude/skills/run-shunt of pleaseai/shunt.

  • SKILL.md
  • smoke.sh
  • test_smoke.sh

Open the folder on GitHubat commit e147f9b

Compare with similar skills

Run Shunt next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Run Shunt compared with similar skills
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Run Shunt this skillpleaseai/shunt281—~2.6kAutomated safety check: PassApache-2.0
Provider Integrationhex/claude-council851—~635Automated safety check: PassMIT
Embeddings via 9Routerdecolua/9router30k—~604Automated safety check: PassMIT
Pulse Releasequnqin24/Pulse517—~1.3kAutomated safety check: PassApache-2.0
Using Ccproxy Inspectorstarbaser/ccproxy350—~2.7kAutomated safety check: PassCustom licence
Bridgic LLMsbitsky-tech/bridgic155—~839Automated safety check: NotesMIT

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Categories

Questions about Run Shunt

What does Run Shunt do?

Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy). Run Shunt is an agent skill from pleaseai/shunt. Build, launch, and drive shunt — the Claude Code LLM gateway (a Rust/axum Anthropic-Messages proxy).

When should I use Run Shunt?

Run Shunt fits situations like: curl-drive the gateway; exercise /v1/models discovery and /v1/messages proxying; connect Claude Code to a local shunt instance.

How do I install Run Shunt in Claude Code?

Run `npx skills add pleaseai/shunt --skill run-shunt -a claude-code`. Or copy the skill folder (.claude/skills/run-shunt in pleaseai/shunt) into .claude/skills/run-shunt in your project. Claude Code loads it when a task matches its description.

How do I install Run Shunt in Codex?

Run `npx skills add pleaseai/shunt --skill run-shunt -a codex`. Or copy the skill folder (.claude/skills/run-shunt in pleaseai/shunt) into .agents/skills/run-shunt in your project. Codex loads it when a task matches its description.

Can I use Run Shunt in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pleaseai/shunt --skill run-shunt -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/run-shunt, .gemini/skills/run-shunt, .github/skills/run-shunt and .opencode/skills/run-shunt in your project.

What does Run Shunt need to run?

Going by SKILL.md and its folder, Run Shunt needs a shell for the scripts in its folder, the command-line tools its instructions call (cargo, jq, curl, python3, claude and apt-get) and credentials named ANTHROPIC_AUTH_TOKEN. Our summary lists: Python 3; A Bash shell; A credential in ANTHROPIC_AUTH_TOKEN.

Does Run Shunt access the network?

SKILL.md names 2 domains. As links in the text: github.com and code.claude.com. This is read from the text; nothing was executed.

Is Run Shunt safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Run Shunt use?

Run Shunt is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Run Shunt use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Run Shunt?

Skills that share tags, products or a category with Run Shunt: Provider Integration (hex/claude-council, 851 stars), Embeddings via 9Router (decolua/9router, 30k stars), Pulse Release (qunqin24/Pulse, 517 stars) and Using Ccproxy Inspector (starbaser/ccproxy, 350 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Run Shunt?

pleaseai (a GitHub organization) maintains it in pleaseai/shunt, which has 281 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 8, 2026.

Source: pleaseai/shunt on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.