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.
curl -O https://raw.githubusercontent.com/wanghao9610/STAR/main/.agents/skills/star-plan-reviser/SKILL.mdgit clone --depth 1 https://github.com/wanghao9610/STARWrote 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/skills/wanghao9610/star/star-plan-reviser)<a href="https://agentmods.dev/skills/wanghao9610/star/star-plan-reviser"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-plan-reviser/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.
<a href="https://agentmods.dev/skills/wanghao9610/star/star-plan-reviser"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-plan-reviser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00051 | $0.03658 |
| Opus 5.5 | $0.00020 | $0.01463 |
| Sonnet 5.5 | $0.00010 | $0.00732 |
| Haiku 4.5 | $0.00005 | $0.00366 |
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.
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.
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
- Evidence before opinion. Every review claim carries an evidence pointer (file path, log line, command output). A log's self-reported
doneis 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. - 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.mdand never writes or proposes revisions. Synthesis and judgment stay with the main agent. - 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.
- Revise in place, leave a trail. Approved edits go into the original
<prefix>_<slug>_plan.md; never fork_v2copies (a duplicate prefix breaks the tree status/decomposer/executor parse). Each session appends one## Revision Historyentry (date, per-change one-liners with evidence, report path) and bumpsupdated; older versions live in git. - 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 tostar-plan-decomposer, research-question or method pivots tostar-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. - Knock-on effects. A revision can invalidate work built on the old text. Point out reverse
depends_onedges and derived children before asking for changes (report §6); sync the parent's## Sub-plansone-liner when the objective line changes; the bumpedupdatedletsstar-flow-statusshow staleness downstream.
What ships with it
10 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.
- agents/openai.yaml 62 B
- assets/review_report_template_zh.md 2.8 KB
- assets/review_report_template.md 2.9 KB
- references/drop_rules_zh.md 7.9 KB
- references/drop_rules.md 7.9 KB
- references/review_spec_zh.md 5.9 KB
- references/review_spec.md 6.1 KB
- references/revision_rules_zh.md 6.4 KB
- references/revision_rules.md 6.5 KB
- scripts/scan.sh 25 KB runs code
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.
- 14d ago Changed · +2 lines aec53a70b4cf
- 1mo ago Changed · +6 lines 9d7a1a7cc547
- 2mo ago Changed · -24 lines · -123 tokens per session 15f6b6142205
- 2mo ago First seen · 133 lines · 174 tokens per session scan A 8aa6650683ee
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.
star-plan-reviser compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| star-plan-reviserwanghao9610/STAR | Skill | 54 | 2d ago | MIT | A | 51 | Codex |
| create-workflowLazyAGI/LazyMind | Skill | 589 | yesterday | Apache-2.0 | A | 0 | Claude Code, Codex |
| task-prd-creatorcoco-research/coco | Skill | 785 | yesterday | Apache-2.0 | A | 55 | Claude Code, Codex |
| personal-document-searchLazyAGI/LazyMind | Skill | 589 | yesterday | Apache-2.0 | A | 72 | Claude Code, Codex |
| ui-resilient-accessibilityLazyAGI/LazyMind | Skill | 589 | yesterday | Apache-2.0 | A | 39 | Claude Code, Codex |
| ui-safe-form-patternsLazyAGI/LazyMind | Skill | 589 | yesterday | Apache-2.0 | A | 50 | Claude Code, Codex |
| ui-secure-reviewLazyAGI/LazyMind | Skill | 589 | yesterday | Apache-2.0 | A | 51 | Claude Code, Codex |