star-auto

star-auto is a skill for Codex from wanghao9610/STAR. It costs 41 tokens per session (741 once invoked), scanned A, original, MIT.

A command that drives a STAR workflow toward a stated goal. STAR is a project-specific system whose next tasks are defined in its command files.

In plain words
What is it for?
Use it only with an explicit $star-auto request, giving it a goal and optionally a stopping point or involvement level.
Why use it?
It helps continue the selected workflow automatically, so you do not need to start each next research task yourself.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Codex; $skill-name invocation.

Good fit Use it only with an explicit $star-auto request, giving it a goal and optionally a stopping point or involvement level.

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Install with agentmods
npx agentmods add skills/wanghao9610/star/star-auto
Install

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.

Any agent
npx skills add wanghao9610/STAR --skill star-auto
Clone the repo
git clone --depth 1 https://github.com/wanghao9610/STAR

Made for: Codex.

Wrote 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.

agentmods badge for star-auto

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanghao9610/star/star-auto/github.svg)](https://agentmods.dev/skills/wanghao9610/star/star-auto)
Your own site
<a href="https://agentmods.dev/skills/wanghao9610/star/star-auto"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-auto/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.

agentmods 80×15 button for star-auto

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanghao9610/star/star-auto"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-auto.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 741 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.00741
Opus 5 $0.00020 $0.00370
Sonnet 5 $0.00008 $0.00148
Haiku 4.5 $0.00004 $0.00074

Measured 2d ago against content hash ec290b4f3c5e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

star-auto 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 2d 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.

.codex/plugins/star/skills/star-auto/SKILL.md · 23 lines

What it actually says

Drive the workflow toward a goal

Read .agents/commands/star-auto.md from the current project root and follow it as the authoritative procedure. When .env sets STAR_LANG=zh, or it is unset and the conversation is in Chinese, use .agents/commands/star-auto.zh-CN.md for the user-facing wording while keeping the English file's decisions.

Adapt its invocation spelling and model routing for Codex:

  • $star-auto <goal> [stop=<stop line>] [involve=<level>] is this command.
  • $star-<name> <argument> is the spelling where the shared file writes /star-<name> <argument>.

For every run that this command starts, resolve its tier and any mode exception under conventions §10.8. Read the corresponding STAR_PLAN_MODEL, STAR_EXEC_MODEL, or STAR_READ_MODEL value once with the opening .env load. In a comma-separated value, take codex:<model> first, otherwise an untagged model; ignore entries tagged for another harness. Split a recognized final @<depth> from the model, retaining an unrecognized @ suffix as part of the model name. An empty result names no model or depth.

When the resolved model is non-empty, this Codex runtime can name a subagent model, and either that model is not an alias of the active session's actual model or the entry carries a supported per-dispatch depth, start the run with spawn_agent: pass the model explicitly and, when the tool and selected model accept it, pass the depth as reasoning_effort. A usable explicit depth triggers this fresh run even when the model is unchanged. Pass fork_turns: "none" whenever the runtime exposes that field, including for blind reads: this runtime does not allow a model or effort override with a full fork. Use the same rule for both unmarked and skills. If a dispatch rejects the requested depth, first confirm it started no work; then retry without reasoning_effort only when the model itself differs, otherwise retain the shared local route, and state once that the depth was not applied. With no routing difference, retain the shared procedure: load and follow an unmarked project star-* skill here, or dispatch the skill's subagent as the shared file requires, without a model or effort override.

Every model- or effort-routed subagent brief is self-contained: tell it to read the selected skill's project SKILL.md in full; include the original skill invocation, its resolved tier=<name> and involve=<level> tokens, auto=unattended when this invocation carries it, and the language resolved from STAR_LANG or the dialogue. Include the active session's actual provenance as a model id only. Never pass the parent session's model-resolver command or treat its output as the child's model provenance: the child resolves and records its own provenance from its own session context. Record the requested depth, or default, beside the tier and actual child model. These routing rules inherit the shared procedure's confirmation, STOP-line, sandbox, and approval limits; they authorize no additional action.

If .agents/commands/star-auto.md is missing, report that the project does not contain the STAR auto procedure instead of guessing from the plugin package.

Files

What ships with it

2 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.

Changes

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.

  1. 2d ago Changed · +4 lines ec290b4f3c5e
  2. 10d ago First seen · 19 lines · 41 tokens per session scan A 6798e9d99361

Subscribe to this mod's changes

star-auto is a skill published in the GitHub repository wanghao9610/STAR (52 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 741 once invoked, about $0.0002 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.

Related

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