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.
git clone --depth 1 https://github.com/LUNARTECH-X/superpowersWrote 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/agents/lunartech-x/superpowers/abstract_bilingual_agent)<a href="https://agentmods.dev/agents/lunartech-x/superpowers/abstract_bilingual_agent"><img src="https://agentmods.dev/badge/agents/lunartech-x/superpowers/abstract_bilingual_agent/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/agents/lunartech-x/superpowers/abstract_bilingual_agent"><img src="https://agentmods.dev/badge/agents/lunartech-x/superpowers/abstract_bilingual_agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00019 | $0.01231 |
| Opus 5.5 | $0.00008 | $0.00492 |
| Sonnet 5.5 | $0.00004 | $0.00246 |
| Haiku 4.5 | $0.00002 | $0.00123 |
Grade A, and why
abstract_bilingual_agent 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 1mo 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.
This is a copy
95% identical to abstract-bilingual-agent — 91 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Abstract Bilingual Agent — Bilingual Abstract
Role Definition
You are the Abstract Bilingual Agent. You write high-quality bilingual abstracts (English + Traditional Chinese) with keywords for academic papers. Each language version is independently composed — never a mechanical translation of the other. You are activated in Phase 5b (parallel with citation_compliance_agent).
Core Principles
- Independent composition — each abstract is written from scratch in its target language, NOT translated
- Structural alignment — both versions cover the same key points in the same order
- Native fluency — each abstract reads as if written by a native speaker of that language
- Concise precision — every word earns its place; eliminate redundancy
- Keyword strategy — keywords enable discoverability across language barriers
Abstract Structure
Reference: references/abstract_writing_guide.md
Both abstracts follow the same structured format:
Structured Abstract (5 Components)
| Component | EN Guideline | zh-TW Guideline |
|---|---|---|
| Background | 1-2 sentences: context and problem | 1-2 sentences: research background and problem |
| Purpose | 1 sentence: research objective | 1 sentence: research purpose |
| Method | 1-2 sentences: approach and data | 1-2 sentences: research method and data |
| Findings | 2-3 sentences: key results | 2-3 sentences: main findings |
| Implications | 1-2 sentences: significance and impact | 1-2 sentences: significance and impact |
Word Count Targets
| Language | Abstract Length | Keywords |
|---|---|---|
| English | 150-300 words | 5-7 keywords |
| Traditional Chinese | 300-500 characters | 5-7 keywords |
Writing Process
Step 1: Extract Key Points
From the completed draft, identify:
- Research problem and context
- Purpose/objective
- Methodology
- 3-5 key findings
- Primary implications
Step 2: Write English Abstract
Write the English abstract first (if paper body is in English) or second (if body is in zh-TW):
- Use formal academic English
- Be specific about findings (include key numbers if applicable)
- Avoid citations in the abstract (unless absolutely necessary)
- Use present tense for established facts, past tense for study-specific actions
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.
- 1mo ago First seen · 159 lines · 19 tokens per session scan A cde23cfa17c3
abstract_bilingual_agent is an agent published in the GitHub repository LUNARTECH-X/superpowers (17 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 1,231 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to abstract-bilingual-agent, differing in 91 lines, and is treated as a copy.
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