Np. Still learning about how to reference agentskills from my coding LLM here. Haven't yet worked with MCP or A2A much. I should port instruction prompts from each project's AGENTS.md to reusable skills in .claude/skills/skillname/SKILL.md ; so that I can reference "/skillname" in a prompt to reuse that prompt text.
Copilot looks for agent skills in .claude/skills/, .github/skills/, or .agents/skills/ .
FWIU there are package managers for agent skills?
PAKS:
https://github.com/stakpak/paks
vercel-labs/skills:
https://github.com/vercel-labs/skills :
export DISABLE_TELEMETRY=1
npx skills add vercel-labs/agent-skills
https://skills.sh/docs/cliA reproducibility, traceability, and auditability concern:
How to show the text of the exact version of the skill referenced in each input prompt in each chat log? GH copilot's JSON export format is a fairly complete trace compared to e.g. Gemini Chat.
.
ElasticSearch (Java) and Meilisearch (Rust) do at least porter stemming before indexing.
MeiliSearch can be used as a vector database for langchain.
meilisearch/meilisearch: https://github.com/meilisearch/meilisearch :
Meilisearch docs > langchain guide > Performing Similarity Search:
https://www.meilisearch.com/docs/guides/langchain#performing...
from langchain.vectorstores import Meilisearch
from langchain.embeddings.openai import OpenAIEmbeddings
meilisearch/meilisearch-mcp :
https://github.com/meilisearch/meilisearch-mcpopenobserve/openobserve :
https://github.com/openobserve/openobserve :
> OpenObserve is an open-source observability platform for logs, metrics, traces, and frontend monitoring. A cost-effective alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment. with SQL in Rust
OpenObserve (AGPL) docs > MCP:
https://openobserve.ai/docs/integration/mcp/ :
> This capability is supported in the Enterprise edition of OpenObserve
https://github.com/openobserve/openobserve/issues/6804
openobserve docs > Comparison with Alternatives >
How does OpenObserve compare to Elasticsearch:
https://openobserve.ai/docs/overview/comparison/
meilisearch blog > "What is GraphRAG: Complete guide [2026]" https://www.meilisearch.com/blog/graph-rag :
> How is GraphRAG different from baseline RAG?
> GraphRAG represents one of the different types of RAG, and its retrieval process differs from baseline RAG.
> Baseline RAG is vector search-based, while GraphRAG uses structured relationships to get the end result. GraphRAG can still use vector and full-text search, but relationships drive what gets retrieved.
/? graphrag sqlite fts : https://www.google.com/search?q=graphrag+sqlite+fts