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.
npx skills add ConmuYan/my-academic-skills --skill awesome-abstractgit clone --depth 1 https://github.com/ConmuYan/my-academic-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/skills/conmuyan/my-academic-skills/awesome-abstract)<a href="https://agentmods.dev/skills/conmuyan/my-academic-skills/awesome-abstract"><img src="https://agentmods.dev/badge/skills/conmuyan/my-academic-skills/awesome-abstract/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/conmuyan/my-academic-skills/awesome-abstract"><img src="https://agentmods.dev/badge/skills/conmuyan/my-academic-skills/awesome-abstract.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 | $0.00127 | $0.01830 |
| Opus 5.5 | $0.00051 | $0.00732 |
| Sonnet 5.5 | $0.00025 | $0.00366 |
| Haiku 4.5 | $0.00013 | $0.00183 |
Grade A, and why
awesome-abstract 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 2mo 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Awesome Abstract
A top-tier abstract is not a compressed introduction. It is a closed-loop argument: one limitation of prior work is named, the method addresses that limitation directly, and the evidence shows the limitation is resolved.
Find ONE precise Gap
→ design the Method around it
→ collect Evidence that tests it
→ write so the reader can see the Gap close
Do not jump to prose. Reconstruct the argument, audit it, then write.
When to use
- Write, rewrite, or critique a CS/AI/ML/NLP/CV abstract
- The current draft reads like a shortened intro or an experiment inventory
- The user wants the Gap–Method–Evidence–Resolution loop made explicit
When not to use
| Request | Use instead |
|---|---|
| Sentence-level English polish only | nature-polishing |
| Full intro / method / experiments draft | nature-writing |
| Novelty / prior-art overlap | scoop-check |
| Literature search | paper-search |
Hard rules
- Do not invent results, metrics, datasets, models, comparisons, or limitations.
- Do not draft the abstract until the Argument Card and evidence map exist.
- One core Gap. Secondary results may appear only as evidence that this Gap closed, not as a second unsolved problem.
- Every major concept introduced early is an anchor and must be answered later. Orphans are deleted, weakened, or given evidence.
- Claim strength may not exceed evidence scope.
- The last sentence must resolve the original Gap, not merely report strong performance.
- If the loop cannot close, deliver the diagnosis and a scaffold with
[EVIDENCE NEEDED: …]. Do not hide the hole in fluent prose.
Mode
| User signal | Mode |
|---|---|
| No usable abstract | write |
| Pastes or names a draft | revise |
| 检查 / 诊断 / audit / 证据链 | audit |
| 先拆逻辑 / extract only | extract |
Default: revise if a draft is present, else write.
Honor a stated venue or word limit. Otherwise write 150–220 words, one paragraph. Use two short paragraphs only for journal abstracts when the venue needs a slightly wider close.
What ships with it
5 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.
- 2mo ago First seen · 212 lines · 127 tokens per session scan A b6e9caf9572e
awesome-abstract is a skill published in the GitHub repository ConmuYan/my-academic-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 127 tokens to every session and 1,830 once invoked, about $0.0005 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 2026-08-31.
awesome-abstract compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| awesome-abstractConmuYan/my-academic-skills | Skill | 2 | 2mo ago | MIT | A | 127 | Claude Code |
| research-paper-reviewBESSER-PEARL/research-agent-skills | Skill | 18 | 17d ago | MIT | A | 87 | Claude Code, Codex |
| html-ppt-zhangzara-pin-and-papernexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 51 | Claude Code, Codex |
| physicsnemo-discoverNVIDIA/physicsnemo | Skill | 3.4k | yesterday | Apache-2.0 | A | 124 | Claude Code, Codex |
| ml-training-recipesOrchestra-Research/AI-Research-SKILLs | Skill | 14k | 27d ago | MIT | A | 88 | Claude Code |
| hdf5-pde-data-loadingsynthetic-sciences/openscience | Skill | 4.3k | 2d ago | Apache-2.0 | A | 82 | Claude Code, Codex |
| deep-learningericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 102 | Claude Code, Codex |