STAR: Skill for Codex

.agents/skills/star-plan-reviser/SKILL.md

star-plan-reviser is a skill for Codex from wanghao9610/STAR. It costs 51 tokens per session (3,658 once invoked), scanned A, original, MIT.

A workflow that checks an existing STAR plan against what was actually completed, then revises the plan with approval for each item.

In plain words
What is it for?
Use it to review a plan in the project’s plan and work directories, compare it with execution evidence, and update the plan item by item.
Why use it?
It helps reveal which planned claims are supported by files, logs, and outputs, instead of treating every planned task as finished.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is wanghao9610/STAR's own configuration. It tells Codex how to work on STAR itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything STAR configures →

Reuse

Borrowing it

Nothing to install: this file belongs to wanghao9610/STAR. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/wanghao9610/STAR/main/.agents/skills/star-plan-reviser/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/wanghao9610/STAR

Made for: Codex.

Wrote this? Show the measurements

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README.md
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Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,658 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 $0.00051 $0.03658
Opus 5.5 $0.00020 $0.01463
Sonnet 5.5 $0.00010 $0.00732
Haiku 4.5 $0.00005 $0.00366

Measured 14d ago against content hash aec53a70b4cf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

star-plan-reviser 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 14d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/scan.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/star-plan-reviser/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Plan Reviser

Invocation: star-plan-reviser PLAN_NAME [DESCRIPTION]. Resolve the plan first. Natural language that clearly gives up or revives the direction selects a drop or a revival and supplies its reason; otherwise run the evidence review. It may also approve named revision items. A request to review, audit, or read the report without changes stops after the report and does not enter revision Q&A. With no settled target, list candidates and ask.

Shared conventions. Follow docs/mds/star-workflow/research-workflow-conventions.md for scope, authority, .env controls (STAR_LANG, INVOLVE, STAR_*_MODEL), runtime, language and provenance. Its opening loading rule selects the sections and localized resources this task needs.

After resolving the target and the drop, revival, or review path, run scripts/scan.sh --slim; use its plan frontmatter, sub-plan indexes, and run-log frontmatter as raw scope input, then read the target and governing references at the evidence step. If it fails, read the plans directly and report the fallback.

Passing a tier model. Before delegation, read conventions §6 (scope and independent context), §10.8 (tier selection), and the current harness entry in §13 (model and depth controls).

Role

Take one plan node, audit its intent against execution evidence, and revise the plan in place only for changes the user has already directed or accepts from the visible candidate list. star-flow-status is the shallow whole-tree view; this skill is the deep single-plan audit.

Revise text; do not re-run experiments, re-decompose subtrees, or re-derive strategy from scratch.

Core Principles

  1. Evidence before opinion. Every review claim carries an evidence pointer (file path, log line, command output). A log's self-reported done is not completion — corroborate it against artifacts on disk, re-running cheap checks where pivotal; never launch heavy experiments (conventions §2's STOP line applies here too). This applies the project's Verification rule (AGENTS.md §11) to the plan itself. Rules: references/review_spec.md.
  2. Collect wide; judgment stays with the main agent. Delegate collection whenever bounded, independent, read-only inspection of several runs or artifact sets materially helps; when it does, dispatch a read-only sub-agent on the READ tier's model (conventions §10.8), where the harness can name one. Any delegate follows the collector format in references/review_spec.md and never writes or proposes revisions. Synthesis and judgment stay with the main agent.
  3. The user owns every change. Findings become numbered revision candidates. Apply any named changes already authorized; put the rest on the page and ask once under conventions §7.13. Every write must trace to an explicit directive or a candidate accepted from that visible list.
  4. Revise in place, leave a trail. Approved edits go into the original <prefix>_<slug>_plan.md; never fork _v2 copies (a duplicate prefix breaks the tree status/decomposer/executor parse). Each session appends one ## Revision History entry (date, per-change one-liners with evidence, report path) and bumps updated; older versions live in git.
  5. Stay inside the family's write discipline. Never renumber prefixes; never touch EXEC_PLAN.md / EXEC_LOG.md (the executor's); structural re-shaping (add/remove sub-plans, redraw the dependency graph) routes to star-plan-decomposer, research-question or method pivots to star-plan-coach — while the target's outline lines, units not yet expanded into files (conventions §0), are text and stay local candidates. Boundaries: references/revision_rules.md.
  6. Knock-on effects. A revision can invalidate work built on the old text. Point out reverse depends_on edges and derived children before asking for changes (report §6); sync the parent's ## Sub-plans one-liner when the objective line changes; the bumped updated lets star-flow-status show staleness downstream.

Read the full file on GitHub · 117 lines

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. 14d ago Changed · +2 lines aec53a70b4cf
  2. 1mo ago Changed · +6 lines 9d7a1a7cc547
  3. 2mo ago Changed · -24 lines · -123 tokens per session 15f6b6142205
  4. 2mo ago First seen · 133 lines · 174 tokens per session scan A 8aa6650683ee

Subscribe to this mod's changes

star-plan-reviser is a skill published in the GitHub repository wanghao9610/STAR (54 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 3,658 once invoked, about $0.0002 per session on Opus 5.5. 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

star-plan-reviser compared with skills from other repositories

star-plan-reviser next to 6 skills from other repositories
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star-plan-reviserwanghao9610/STARSkill542d agoMITA51Codex
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task-prd-creatorcoco-research/cocoSkill785yesterdayApache-2.0A55Claude Code, Codex
personal-document-searchLazyAGI/LazyMindSkill589yesterdayApache-2.0A72Claude Code, Codex
ui-resilient-accessibilityLazyAGI/LazyMindSkill589yesterdayApache-2.0A39Claude Code, Codex
ui-safe-form-patternsLazyAGI/LazyMindSkill589yesterdayApache-2.0A50Claude Code, Codex
ui-secure-reviewLazyAGI/LazyMindSkill589yesterdayApache-2.0A51Claude Code, Codex