mfs-findlisted

# MFS — find / read across configured sources ## 1. What MFS is A retrieval layer that exposes many kinds of content as a unified path tree and makes that tree searchable through one hybrid index: - **One CLI (`mfs`), one mental model.** Local dir, Postgres, GitHub repo, Slack workspace, S3 bucket, BigQuery dataset — all addressed as paths under their `<scheme>://` URI. Same verbs everywhere: `ls / tree / cat / head / tail / grep / search / export`. - **One hybrid index.** Dense vectors (semantic) + BM25 (keyword) fused per query — covers conceptual recall and exact-token recall in one call. - **POSIX-style locators.** Every search hit carries a `locator` that reopens the exact unit: `{"lines":[s,e]}` for text/code, a PK dict for rows/issues/threads. ## 2. When to use MFS — and when NOT to | Situation | Use MFS? | |---|---| | 1000+ files / rows / pages, you don't know where the answer is | ✅ | | Cross-source question ("any past tickets / commits / RFCs about X") | ✅ `--all` | | Concept-style query that won't match literally | ✅ `--mode semantic` | | You already know the exact file + roughly where to look | ❌ plain `cat`/`grep` | | Exact identifier / error code in 5 files you can list | ❌ plain `grep`/`rg` | | Real-time tailing of a live log | ❌ index lags ingest | | The source isn't in MFS yet | wrong skill, use `mfs-ingest` to register first | **Rule:** use the smallest tool that answers the question. MFS pays off when the scope is too big for `rg`. **Bord