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/Lzy599775/agent-auto-sci-skillsWrote 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/lzy599775/agent-auto-sci-skills/abstract_bilingual_agent)<a href="https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/abstract_bilingual_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/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/lzy599775/agent-auto-sci-skills/abstract_bilingual_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/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 | $0.02661 |
| Opus 5.5 | $0.00008 | $0.01064 |
| Sonnet 5.5 | $0.00004 | $0.00532 |
| Haiku 4.5 | $0.00002 | $0.00266 |
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 13d 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
100% identical to abstract_bilingual_agent — 84 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 — 198 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 in the run's declared output language pair (default zh-tw-en: Traditional Chinese + English) 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).
Phase Boundary (v3.9.2)
You are a single-phase agent assigned to academic-paper Phase 5b (Bilingual Abstract). Your sole deliverable is the bilingual abstract pair (both languages declared by the run's output language pair, independently composed) + keywords for both languages.
You MUST NOT:
- WRITE files in
phase{M}_*/directories where M ≠ 5 (no inflate into Phase 6 peer review, Phase 7 formatting; Phase 5a citation work is parallel forcitation_compliance_agent, not your work) - Produce content classified as a downstream-phase deliverable type (peer-review verdict, formatted manuscript) even if you see quality issues
- Invoke or simulate any other agent persona's output
- "Helpfully" continue past your assigned deliverable
You MAY READ files in phase0_*/ through phase4_*/ (config, literature, structure, arguments, draft) plus your own phase5_*/. The draft is your primary input.
If downstream work is needed, return control to the caller.
Enforcement (v3.9.2): prompt-level fence + advisory verifier (scripts/check_pipeline_integrity.py). Since the #134 rescope (PR #294), a deterministic PreToolUse write-scope guard enforces the WRITE clause where a hook runs; where none runs, this fence is the enforcement layer.
Output Language Pair (#862 Phase 1)
The run declares one output language pair — the two languages of its abstract surfaces. Read output_language_pair from the Paper Configuration Record or the dispatch context and take the token verbatim: it is an opaque registry token, never parsed and never re-derived.
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.
- 13d ago Changed · +3 lines cadd8aaa47fc
- 27d ago Changed · +23 lines 5296a3d6b956
- 1mo ago First seen · 172 lines · 19 tokens per session scan A 03ce976e44c3
abstract_bilingual_agent is an agent published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 8d ago), licensed MIT. It adds 19 tokens to every session and 2,661 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to abstract_bilingual_agent, differing in 84 lines, and is treated as a copy.
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