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Take a tolerance break or quit cannabis with streak tracking and craving support
Extract and structure data from documents about the illegal antiquities trade, including dealers, collectors, artifacts, locations, and relationships. Use when processing news reports, academic articles, legal documents, encyclopedia entries, or research materials pertaining to looted artifacts, antiquities trafficking, provenance research, or cultural heritage crimes. Returns structured JSON with entities (persons, organizations, artifacts, locations) and their relationships.
Extract and structure data from documents about the illegal antiquities trade, including dealers, collectors, artifacts, locations, and relationships. Use when processing news reports, academic articles, legal documents, encyclopedia entries, or research materials pertaining to looted artifacts, antiquities trafficking, provenance research, or cultural heritage crimes. Returns structured JSON with entities (persons, organizations, artifacts, locations) and their relationships.
Generates image generation prompts for Xiaohongshu covers based on user content. It polishes the content to fit Xiaohongshu style + applies a visual style template to produce a JSON output for image generation.
Extract and structure data from documents about the illegal antiquities trade, including dealers, collectors, artifacts, locations, and relationships. Use when processing news reports, academic articles, legal documents, encyclopedia entries, or research materials pertaining to looted artifacts, antiquities trafficking, provenance research, or cultural heritage crimes. Returns structured JSON with entities (persons, organizations, artifacts, locations) and their relationships.
- `docs/`: Docusaurus tutorials plus a Rust crate for doctesting tutorial markdown.
Documentation for the `Mastra.listStoredAgents()` method in Mastra, which retrieves a paginated list of agents from storage.
Salience Delegation & Latent Horizon Preservation
- **Integration tests using a real database must clean up after themselves** — tests run against shared Neon branches. Always delete created rows in `afterAll` so other test suites aren't affected by leftover data. Tests using mock repositories (`createMockContainer`) do not need cleanup.
Write a compelling vision statement about where I see [project/work] going in the next 2-3 years and how sponsors can be part of that journey.
Write an announcement for my Sponsors page about a new milestone or feature in [project], encouraging new and existing sponsors to get involved.
Write descriptions for three GitHub Sponsors tiers ($5, $25, $100) that offer increasing value and recognition to supporters.
Write a GitHub Sponsors bio for my profile that highlights my experience in [your field], the impact of my open source work, and my commitment to community growth.
A core intuition and opinion baked into the design of VLM Caption is that multi-turn conversation can help extract superior information by allowing different questions to be asked, then bring them together with a final summary request. Other VLM scripts or apps are likely just trying to "one shot"
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Generates image generation prompts for Xiaohongshu covers based on user content. It polishes the content to fit Xiaohongshu style + applies a visual style template to produce a JSON output for image generation.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.