Classify content by epistemic strength using GMIF levels and persist claims in PostgreSQL with pgvector.
npx skills add https://github.com/rodolfomatos/grilo-falante --skill grilo-falante
Please help me install this Agent Skill. Skill: grilo_falante Source: https://github.com/rodolfomatos/grilo-falante/tree/main Command: npx skills add https://github.com/rodolfomatos/grilo-falante --skill grilo-falante
The Grilo Falante skill provides a lightweight workflow to analyze content by applying GMIF classification, persist results across sessions in PostgreSQL with pgvector, and assign GF-IDs for traceable governance.
Load the regime with grilo_load() and grilo_acordar(temporal_anchor="YYYY-MM-DD", intention="...") and then feed content to the grilo_falante skill to analyze and persist GMIF-classified claims with GF-IDs.
High-intent search queries and answers about installing and using this skill.
To classify and persist epistemic claims in PostgreSQL, you can use this Skill to apply GMIF levels (M1-M7) to content, store results with pgvector support, and assign stable GF-IDs for cross-session traceability and rollback.
GMIF classification is a method of labeling content by epistemic strength using levels M1 through M7. It tracks claim provenance by assigning GF-IDs, enabling structured auditing and cross-session evidence evolution tracking.
You analyze documents by loading the regime with grilo_load() and grilo_acordar(), then feeding content to the Skill. It automatically labels claims with GMIF strength and persists them in PostgreSQL for retrieval.
Yes, pgvector supports vector search for epistemic governance by enabling cross-session retrieval of GMIF-classified claims. This allows analysts to query persisted evidence and track context evolution within the database.
Yes, you can audit GMIF distributions across multiple sessions because the Skill persists claims, context, and GF-IDs in PostgreSQL. This cross-session memory outputs a structured representation suitable for auditing and rollback.
The primary constraint is the dependency on PostgreSQL with pgvector for persistent memory. Without this database environment configured, the Skill cannot store GMIF distributions, assign GF-IDs, or support cross-session traceability.
yoanbernabeuConfigure PostgreSQL with pgvector for GrepAI storage backends.
QSong-githubRetrieve FDA DILIrank and DILIst records by drug name, LTKB ID, or DILIst ID.
QventuRetrieve information from ExuluContext tables using hybrid PostgreSQL search.
rahulgupta2018Designs persistent memory architectures for agent systems with cross-session retention and entity tracking.
