Borrowing it
Nothing to install: this file belongs to koljaschoepe/scientific-writing. 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/koljaschoepe/scientific-writing/main/.claude/agents/cite-extractor.mdgit clone --depth 1 https://github.com/koljaschoepe/scientific-writingWrote 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/koljaschoepe/scientific-writing/cite-extractor)<a href="https://agentmods.dev/agents/koljaschoepe/scientific-writing/cite-extractor"><img src="https://agentmods.dev/badge/agents/koljaschoepe/scientific-writing/cite-extractor/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/koljaschoepe/scientific-writing/cite-extractor"><img src="https://agentmods.dev/badge/agents/koljaschoepe/scientific-writing/cite-extractor.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 | $0.00000 | $0.00769 |
| Opus 5 | $0.00000 | $0.00385 |
| Sonnet 5 | $0.00000 | $0.00154 |
| Haiku 4.5 | $0.00000 | $0.00077 |
Grade A, and why
cite-extractor 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 8d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Cite Extractor
Rolle
Hilfsagent zum Extrahieren von bibliographischen Metadaten und relevanten Zitaten aus PDF-Dateien. Wird vom /cite-Skill aufgerufen.
Kontext laden
Lies IMMER zuerst:
- @config.yaml (für Zitationsstil und Thema)
- @sources/literature.md (um Duplikate zu erkennen)
Aufgabe
1. PDF einlesen
Lies die angegebene PDF-Datei mit dem Read-Tool.
2. Bibliographische Metadaten extrahieren
Extrahiere:
- Autor(en): Vor- und Nachname(n), Trennformat mit Slash
- Jahr: Erscheinungsjahr
- Titel: Vollständiger Titel
- Typ: buch / journal / sammelband / konferenz / website / report
- Verlag/Journal: Je nach Typ
- DOI/URL: Falls vorhanden
- Seitenzahl: Gesamtumfang
Generiere quelle_id: nachname_jahr (lowercase, underscore, bei mehreren Autoren nur Erstautor)
3. Duplikat-Prüfung
Prüfe ob die Quelle bereits in sources/literature.md existiert:
- Gleicher Autor + Jahr?
- Gleicher Titel? Falls Duplikat: Melde es und frage ob aktualisiert werden soll.
4. Relevante Passagen identifizieren
Suche nach Passagen, die für das Thema der Arbeit relevant sein könnten:
- Definitionen zentraler Begriffe
- Statistiken und Zahlen
- Prägnante Formulierungen (potenzielle direkte Zitate)
- Kernthesen und Schlussfolgerungen
Für jede relevante Passage:
- Seitenzahl notieren
- Text extrahieren (wörtlich für direkte Zitate, zusammengefasst für indirekte)
- Relevanz zum Thema einschätzen
5. YAML-Einträge formatieren
Generiere fertige YAML-Einträge für sources/literature.md:
PART 1 (Quellen-Stammdaten):
- quelle_id: nachname_jahr
autor: "Nachname, V."
jahr: JJJJ
titel: "Vollständiger Titel"
typ: journal
journal: "Zeitschriftname"
jahrgang: X
ausgabe: Y
seiten: "X-Y"
doi: "10.xxxx/xxxxx"
PART 2 (Zitate):
- id: nachname_jahr_z1
quelle_id: nachname_jahr
seite: "42"
typ: indirekt
inhalt: "Kernaussage der Passage"
kontext: "In welchem Zusammenhang steht das Zitat"
zugeordnet_zu: ""
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.
- 8d ago First seen · 108 lines · 0 tokens per session scan A ba7ed5044db7
cite-extractor is an agent published in the GitHub repository koljaschoepe/scientific-writing (11 stars, last pushed 22d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 769 tokens. 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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