shiro-neko/docs/configuration.md

Configuration

Settings come from three places. Later wins:

1. ~/.shiro-neko/config.json
2. environment variables
3. command-line flags

The config file

Written by /provider, editable by hand. Every field is optional.

{
  "provider": "openai",
  "model": "gpt-5",
  "baseURL": "https://api.openai.com/v1",
  "apiKey": "sk-...",
  "presetId": "openai",
  "agent": "default",
  "thinking": "medium",
  "maxRetries": 3,
  "plugins": ["guard", "time"],
  "toolSets": ["edit-plus", "git"],
  "permission": {
    "bash": { "*": "ask", "git *": "allow" }
  },
  "registryUrl": "https://example.com/my-registry/index.json",
  "subagentModel": "claude-sonnet-4-5",
  "mcpServers": {
    "fs": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "."] }
  }
}

Field	Meaning
provider	wire protocol: anthropic or openai. Not the vendor — Groq, OpenRouter, and Ollama all speak openai
model	model id as the endpoint names it
baseURL	API root. Defaults to the official endpoint for the provider
apiKey	sent as Authorization: Bearer for openai, x-api-key for anthropic
presetId	which preset /provider chose, so it can show what is configured
agent	default variant: default, quick, deep, plan, review
thinking	default level: off, low, medium, high, max
maxRetries	retries per model call for transient failures. Default 3
plugins	which builtin plugins to enable. Omit for ["guard", "time"]
toolSets	optional tool sets beyond core: edit-plus, git, and net. Omit for the defaults; net is opt-in. See tools
permission	which calls run, ask, or are refused, matched per command or path. See permissions
registryUrl	index for /registry. Omit for the default. See registry
subagentModel	model used for task subagents. Omit to reuse the parent model. A cheaper model here cuts subagent cost (and latency) sharply for read-only searches. See agents
mcpServers	see MCP

Provider presets

/provider offers these. Each sets baseURL and the wire protocol for you.

Preset	Protocol	Endpoint	Env var checked
Anthropic	anthropic	api.anthropic.com/v1	ANTHROPIC_API_KEY
OpenAI	openai	api.openai.com/v1	OPENAI_API_KEY
OpenRouter	openai	openrouter.ai/api/v1	OPENROUTER_API_KEY
Groq	openai	api.groq.com/openai/v1	GROQ_API_KEY
DeepSeek	openai	api.deepseek.com/v1	DEEPSEEK_API_KEY
xAI	openai	api.x.ai/v1	XAI_API_KEY
Ollama	openai	localhost:11434/v1	none, keyless
LM Studio	openai	localhost:1234/v1	none, keyless
Custom OpenAI-compatible	openai	you supply it	none
Custom Anthropic-compatible	anthropic	you supply it	none

provider is the wire protocol, not the vendor. Groq, DeepSeek, xAI, OpenRouter, Ollama, and LM Studio all speak openai; only Anthropic speaks anthropic. Two things differ between them: the auth header (Authorization: Bearer versus x-api-key), and how thinking levels map.

After the key is entered, GET /v1/models is called and the list becomes a picker. Both protocols expose that endpoint with the same data[].id shape, so one code path handles both. If the endpoint does not implement it, a preset with a known model list falls back to that; otherwise you type the model id and setup still completes.

Anything the picker offers is a model the endpoint actually reports, which is more reliable than a hard-coded list — that is why the fallback lists are short and only exist for Anthropic and OpenAI.

Cost estimates

/cost and the status bar price a turn from a table in src/pricing.ts, matched by longest prefix on the model id, so claude-sonnet-4-5-20250929 resolves via claude-sonnet-4-5. An OpenRouter-style anthropic/claude-sonnet-4-5 has its vendor prefix stripped first.

An unknown model is reported as unpriced rather than guessed:

4210 in / 88 out tokens (llama-3.3-70b is unpriced)

Two limits worth knowing. The rates are hand-entered and drift as vendors change them, so treat the figure as an estimate, not a bill. And the token counts come from the provider's usage report, while ~ctx in the status bar is JSON.stringify(messages).length / 4 — good enough to decide when to compact, wrong enough that it should not be read as a token count.

Environment variables

Variable	Effect
SHIRO_PROVIDER	overrides provider
SHIRO_MODEL	overrides model
SHIRO_BASE_URL	overrides baseURL
SHIRO_API_KEY	overrides apiKey
ANTHROPIC_API_KEY	used when provider is anthropic and no key is set
OPENAI_API_KEY	used when provider is openai and no key is set
SHIRO_HOME	relocates config, sessions, memory, history, user skills, and installs
SHIRO_INSTALL_DIR	where install:local and the installers put the binary
SHIRO_REPO	which GitHub repo the installers download from
SHIRO_VERSION	pins the version the installers fetch

SHIRO_HOME is what the test suite uses to keep a run out of your real config. It is also the way to run two isolated setups side by side — a work profile and a personal one — since it moves every piece of state at once:

SHIRO_HOME=~/work-shiro shiro

A key on the command line ends up in your shell history and in ps. SHIRO_API_KEY in front of one command is better; /provider writing to config.json is better still.

Flags

shiro [options]
shiro -p "prompt"          headless, prints to stdout
cat file | shiro -p        prompt read from stdin

Flag	Effect
-p, --print [prompt]	headless mode. Needs --yolo for tool use
--json	with -p, one JSON event per line
-c, --continue	resume the newest session for this directory
-r, --resume <id>	resume by session id or unique prefix
--agent <name>	default, quick, deep, plan, review
--think <level>	off, low, medium, high, max
--provider <name>	anthropic or openai
--model <id>	model id
--base-url <url>	API root
--no-mcp	skip MCP servers
--no-subagent	omit the task tool
--no-instructions	ignore AGENTS.md and friends
--no-skills	ignore builtin, installed, and project skills
--no-plugins	disable all plugins, builtin and installed, including the guard
--no-memory	do not load or write project memory
--yolo	skip every approval prompt
-v, --version	version, bun version, platform, source or compiled
-h, --help	usage

The --no-* flags exist for isolating a problem. All six together strip the agent to its built-in tools and nothing else, which answers "is this the loop or something layered on it?" in one run:

shiro --no-plugins --no-skills --no-memory --no-instructions --no-subagent --no-mcp

--no-plugins also disables the guard, so rm -rf becomes an ordinary approval prompt. Reasonable while debugging, not something to leave on.

An unknown value fails at startup with the valid list rather than falling back silently:

$ shiro --agent turbo
shiro: Unknown agent "turbo". Available: default, quick, deep, plan, review

Where things live

~/.shiro-neko/
  config.json                 provider, model, key, defaults
  sessions/<uuid>.json        transcripts, token counts, cost, task list
  memory/<hash>.json          durable per-project notes
  history/<hash>.json         prompt history for up-arrow recall
  skills/*.md                 your own skills
  registry/skills/*.md        skills installed with /registry
  registry/plugins/*.json     plugin manifests installed with /registry

Project files:

<project>/
  AGENTS.md                   instructions injected into the system prompt
  .shiro/skills/*.md          project skills, override user and builtin
  .shiroignore                extra ignore rules on top of .gitignore

Memory and history file names are SHA-256 prefixes of the absolute project path, because a path is not a safe filename. Two consequences: moving a project loses its memory and history, and two checkouts of the same repo at different paths keep separate ones.

OpenAI reasoning models

Newer OpenAI models reject function tools on /v1/chat/completions and require /v1/responses. For api.openai.com both are chained: a 400, 404, 405, 415, 422, or 501 on the first switches to the second, sticks for the rest of the session, and prints one notice. Retryable failures — 429 and 5xx — are left to the SDK's backoff instead.

Only those six codes qualify, because they mean "this endpoint cannot serve this request shape". A 401 is a wrong key and switching endpoints would only produce a second 401 with a more confusing message.

The switch is sticky on purpose: once an endpoint rejects the shape it rejects every later step too, so re-probing would waste a round trip per step of every turn.

Third-party endpoints get a plain chat-completions model with no fallback probe, since they do not implement /v1/responses.

The two endpoints also differ in how they carry assistant history, which is where compaction gets interesting — see memory.

Config that changes behaviour subtly

Four fields do more than they look like they do.

thinking costs money and latency on every turn, not just hard ones. off on a hard problem produces confident wrong answers; max on a rename wastes cents and seconds. The agent variants already pick sensible levels — see agents.

toolSets removes tools from the model's view entirely. If the agent stops using a tool you expected, check the startup header for which sets loaded: an unrecognised name is dropped silently, so "gti" reads as "git is off". See tools.

permission replaces a tool's defaults rather than merging with them, so { "read_file": { "*": "allow" } } also allows reading .env. Order inside a rule table decides the outcome, since later rules win. See permissions.

registryUrl is the whole trust decision for installed skills and plugins. There are no signatures, so pointing it at an index means trusting whoever controls that URL — including for whatever they publish later. See registry.