create-sentence-markup
Grammarly-like sentence decomposition with NVIS confidence colors. Decomposes question text into annotated fragments showing which entities resolved, which are misspelled, which are fabricated, and which are unknown. Composes /extract-entities for grounding data and /interview for "Did you mean?" clarify prompts.
معلومات المصدر
- المستودع
- grahama1970/agent-stack-public
- آخر نشاط في المصدر
- ٢٤ سبتمبر ٢٠٢٦ في ١٥:٥١
- لغة SKILL.md المكتشفة
- الإنجليزية
- النجوم
- ٠
- التفرعات
- ٠
خيارات التثبيت
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
مراجعة ملفات المصدر
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
مستكشف الملفات
4 ملفاتعرض SKILL.md
SKILL.md
تعليمات المصدر · معاينة للقراءة فقط- name
- create-sentence-markup
- description
- Grammarly-like sentence decomposition with NVIS confidence colors. Decomposes question text into annotated fragments showing which entities resolved, which are misspelled, which are fabricated, and which are unknown. Composes /extract-entities for grounding data and /interview for "Did you mean?" clarify prompts.
- allowed-tools
- ["Bash","Read"]
- triggers
- ["markup sentence","annotate sentence","sentence markup","create sentence markup","grammarly","highlight entities"]
- metadata
- {"short-description":"NVIS-colored sentence annotation from entity grounding","author":"Claude","version":"0.1.0"}
- provides
- ["sentence-markup"]
- composes
- ["extract-entities","interview","agentic-evals"]
- disciplines
- ["extraction","ui-design-engineering"]
# /create-sentence-markup
Grammarly-like sentence decomposition with NVIS confidence colors (MIL-STD-3009).
## Usage
```bash
# Annotate a question — returns JSON annotations
./run.sh annotate "How does SPARTA control X23-MUSTARD mitigate spoofing?"
# Annotate with rendered markdown output
./run.sh annotate "How does the SPRTA framework work?" --format markdown
# Annotate with HTML output (NVIS colors)
./run.sh annotate "What countermesures protect firmware?" --format html
# Pipe from /extract-entities (skip redundant extraction)
./run.sh annotate --entities-json entities.json "How does X23-MUSTARD work?"
```
## Output (JSON default)
```json
{
"text": "How does SPARTA control X23-MUSTARD mitigate spoofing?",
"annotations": [
{
"term": "X23-MUSTARD",
"level": "RED",
"label": "fabricated ID — not in corpus",
"action": "reject",
"closest_match": "CM0028"
},
{
"term": "SPARTA",
"level": "GREEN",
"label": "confirmed framework",
"action": null
}
],
"summary": {
"total_annotations": 2,
"red": 1,
"amber": 0,
"yellow": 0,
"green": 1,
"needs_clarify": 0,
"needs_reject": 1
}
}
```
## NVIS Color System (MIL-STD-3009)
| Level | Color | RGB | Meaning | Action |
|-------|-------|-----|---------|--------|
| GREEN | Green | (0,255,136) | Exact match — confirmed in corpus | None |
| AMBER | Amber | (255,170,0) | Fuzzy match or misspelling | /memory clarify via /interview |
| RED | Red | (255,68,68) | Fabricated ID — not in corpus | Reject |
| YELLOW | Yellow | (255,230,0) | Term not found anywhere | Investigate |
## Composition
- **Input**: Question text (string)
- **Depends on**: `/extract-entities` → `get_annotations()` for grounding data
- **Triggers**: `/interview` for AMBER "Did you mean?" clarify prompts
- **Consumed by**: `/create-evidence-case` (report grounding), `/ask` (inline annotations),
`/lean4-prove` (proof obligations from RED/YELLOW annotations)
## Output Formats
| Format | Flag | Use case |
|--------|------|----------|
| JSON | `--format json` (default) | Machine-readable, piping to other skills |
| Markdown | `--format markdown` | Agent/human readable in terminal |
| HTML | `--format html` | Rich rendering with NVIS colors |
عرض على GitHub