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-executor/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-executor)<a href="https://agentmods.dev/skills/wanghao9610/star/star-plan-executor"><img src="https://agentmods.dev/badge/skills/wanghao9610/star/star-plan-executor.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 73 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00057 | $0.06117 |
| Opus 5 | $0.00028 | $0.03059 |
| Sonnet 5 | $0.00011 | $0.01223 |
| Haiku 4.5 | $0.00006 | $0.00612 |
Grade A, and why
star-plan-executor 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 today.
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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Plan Executor
Invocation: star-plan-executor PLAN_NAME [DESCRIPTION]. Resolve the leaf by slug, numeric prefix, or filename. Remaining natural language may constrain scope or explicitly authorize execution choices; ask only when the target, research scope, acceptance criteria, cost, key inputs, destructive action, or overwrite remains unresolved.
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: explicit user request first, then valid STAR_LANG, then 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.
After resolving the target, run scripts/scan.sh --slim and treat its plan-frontmatter and run-log-frontmatter digest as raw input to Steps 0–1; still read the target leaf in full. If the script fails, read the plan files directly and report the fallback.
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. With an empty value, omit the model override and preserve the host/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.
What ships with it
25 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 63 B
- assets/exec_log_template_zh.md 3.9 KB
- assets/exec_log_template.md 4.2 KB
- assets/exec_plan_template_zh.md 4.0 KB
- assets/exec_plan_template.md 4.3 KB
- references/agent_dispatch_spec_zh.md 6.1 KB
- references/agent_dispatch_spec.md 6.6 KB
- references/branch_rules_zh.md 11 KB
- references/branch_rules.md 12 KB
- references/design_check_zh.md 4.3 KB
- references/design_check.md 4.4 KB
- references/exec_rubric_zh.md 3.4 KB
- references/exec_rubric.md 3.6 KB
- references/orient_checklist_zh.md 2.0 KB
- references/orient_checklist.md 2.0 KB
- references/plan_sync_rules_zh.md 6.9 KB
- references/plan_sync_rules.md 7.6 KB
- references/resume_rules_zh.md 4.4 KB
- references/resume_rules.md 4.8 KB
- references/sizing_check_zh.md 1.9 KB
- references/sizing_check.md 1.8 KB
- references/stop_line_rules_zh.md 4.0 KB
- references/stop_line_rules.md 4.4 KB
- scripts/scan.sh 24 KB runs code
- SKILL_zh.md 25 KB
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.
- today Changed · -7 lines · -114 tokens per session 398ea7c5b770
- 5d ago Changed a6bd1c305970
- 8d ago First seen · 127 lines · 171 tokens per session scan A d01af948ec70
star-plan-executor is a skill published in the GitHub repository wanghao9610/STAR (51 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 6,117 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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