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create-text

Deterministic public-domain text corpus chunker with seeded selectors for reproducible sampling across engineering/government corpora.

معلومات المصدر

المستودع
grahama1970/agent-stack-public
آخر نشاط في المصدر
٢٤ سبتمبر ٢٠٢٦ في ١٥:٥١
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
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التفرعات
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خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

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اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
create-text
description
Deterministic public-domain text corpus chunker with seeded selectors for reproducible sampling across engineering/government corpora.
allowed-tools
Bash, Read, Write
triggers
["create text","text chunker","deterministic text","build text bank","select text chunks"]
metadata
{"short-description":"Deterministic corpus text chunker"}
provides
["create-text"]
composes
["ingest-doc","extract-pdf","best-practices-python","agentic-evals"]
complies
["best-practices-skills","best-practices-python"]
disciplines
["data-engineering"]
# /create-text Deterministic public-domain text corpus chunker with seeded selector. ## Quick Start ```bash # Build text banks from extracted datalake corpus ./run.sh build # Build from Wikipedia (specific categories) ./run.sh build --source wikipedia --categories "Cybersecurity" "Avionics" # Get 16 requirement-style text chunks from defense domain, seed 42 ./run.sh select --content-type requirement --domain defense --count 16 --seed 42 # Get prose paragraphs from any domain ./run.sh select --content-type prose --count 8 --seed 7 # List available domains and content types ./run.sh list ``` ## Content Types | Type | Description | Source | |------|-------------|--------| | `prose` | Continuous paragraphs (3+ sentences) | PDF corpus, Wikipedia | | `bullet_list` | Enumerated/bulleted items | PDF corpus | | `requirement` | Unconditional SHALL/MUST clauses | PDF corpus (MIL-STD, ECSS, NASA-STD) | | `conditional_requirement` | When/If/Unless + SHALL guard clauses | PDF corpus (engineering specs) | | `compound_requirement` | SHALL + enumerated sub-obligations | PDF corpus (rare — extractors split blocks) | | `heading` | Section headers at various levels | PDF corpus | | `latex_equation` | Math equations (raw LaTeX or unicode) | PDF corpus (arxiv) | | `table_cell` | Table content fragments | PDF corpus | | `glossary` | Definition-style entries | PDF corpus, Wikipedia | | `footnote` | Footnote/endnote text | PDF corpus | ## Domains Auto-discovered from datalake at `/mnt/storage12tb/extractor_corpus/`. Common domains: `arxiv`, `defense`, `government`, `engineering`, `nasa`, `nist`, `ietf`, `wikipedia`. ## Interface ```python from create_text import create_text # Deterministic: same seed = same output chunks = create_text(content_type="requirement", domain="defense", count=16, seed=42) # Returns: list[dict] with keys: text, content_type, domain, source_doc, block_id ``` ## Banks Built once via `./run.sh build`, stored as JSON at `/mnt/storage12tb/text_banks/`. One file per domain: `defense.json`, `arxiv.json`, `wikipedia.json`, etc. ## Common Mistakes ```bash # WRONG: Generate synthetic text with an LLM # → Use real extracted text for ground truth # WRONG: Random selection without seed # → Always pass a seed for reproducibility # WRONG: Build banks on every call # → Banks are built once and cached. Use ./run.sh build explicitly. ```
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