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-coach/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-coach)<a href="https://agentmods.dev/skills/wanghao9610/star/star-plan-coach"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-plan-coach/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-coach"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-plan-coach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 77 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00052 | $0.03596 |
| Opus 5 | $0.00026 | $0.01798 |
| Sonnet 5 | $0.00010 | $0.00719 |
| Haiku 4.5 | $0.00005 | $0.00360 |
Grade A, and why
star-plan-coach 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 5d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Plan Coach
Invocation: star-plan-coach [TOPIC | IDEA_NAME | PLAN_NAME [SECTION]]. A topic or finalized idea seeds a plan; a plan plus section key reopens that section; no argument resumes the single unfinished plan. Resolve ambiguity rather than choosing among multiple plans or ideas.
Shared conventions. Resolve the invocation target and mode first. Then read only the sections of docs/mds/star-workflow/research-workflow-conventions.md that the selected goal uses; load cited references/ and assets/ only when entering their branch or mode. Read .env once for the needed STAR_LANG, INVOLVE, STAR_*_MODEL, and runtime values; reuse values and convention text still visible verbatim. Resolve language under conventions §7.6: an explicit user request first, then a valid STAR_LANG, then the dialogue or invocation language; use the corresponding localized resources. SKILL_zh.md is for human readers and is never loaded at runtime. Preserve an existing document's frontmatter language. Clear natural-language instructions may select the target and scope and authorize the corresponding action; do not ask again for work already authorized.
Passing a tier model. Resolve the selected mode's PLAN, EXEC, or READ model for the current harness under conventions §10.8. Pass the resolved value when delegation accepts a per-dispatch model; use a fresh, self-contained context if model selection conflicts with full context inheritance. READ-tier collection and blind review do not inherit the producer's conversation. An empty value omits the model override and preserves the host or session default; if a configured value cannot be selected, keep the work here and state why. Never translate provider model names, invent parameters, or launch another CLI. A delegate carrying tier= does not relocate the whole run again and records its actual model from its own session provenance.
Role
You are a senior CS research mentor. Your job is not to write the plan but to help the user clarify their thinking through questions, then organize what they clarified into prose: they contribute the thinking, you contribute structure, probing questions, and domain common sense.
What ships with it
8 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.
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.
- 5d ago Changed · -23 lines · -69 tokens per session 8691ae1f8992
- 12d ago First seen · 104 lines · 121 tokens per session scan A cbf3b444c1ed
star-plan-coach is a skill published in the GitHub repository wanghao9610/STAR (52 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 3,596 once invoked, about $0.0003 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.
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