Three new tools for structural graph health:
- fix-categories: rule-based recategorization fixing core inflation
(225 → 26 core nodes). Only identity.md and kent.md stay core;
everything else reclassified to tech/obs/gen by file prefix rules.
- cap-degree: two-phase degree capping. First prunes weakest Auto
edges, then prunes Link edges to high-degree targets (they have
alternative paths). Brought max degree from 919 → 50.
- link-orphans: connects degree-0/1 nodes to most textually similar
connected nodes via cosine similarity. Linked 614 orphans.
Also: community detection now filters edges below strength 0.3,
preventing weak auto-links from merging unrelated communities.
Pipeline updated: consolidate-full now runs link-orphans + cap-degree
instead of triangle-close (which was counterproductive — densified
hub neighborhoods instead of building bridges).
Net effect: Gini 0.754 → 0.546, max degree 919 → 50.
New command: `poc-memory triangle-close [MIN_DEG] [SIM] [MAX_PER_HUB]`
For each node above min_degree, finds pairs of its neighbors that
aren't directly connected and have text similarity above threshold.
Links them. This turns hub-spoke patterns into triangles, directly
improving clustering coefficient and schema fit.
First run results (default params: deg≥5, sim≥0.3, max 10/hub):
- 636 hubs processed, 5046 lateral links added
- cc: 0.14 → 0.46 (target: high)
- fit: 0.09 → 0.32 (target ≥0.2)
- σ: 56.9 → 84.4 (small-world coefficient improved)
Also fixes separator agent prompt: truncate interference pairs to
batch count (was including all 1114 pairs = 1.3M chars).
Agents were flying blind — they could see nodes to review and the
topology header, but had no way to discover what targets to link to.
Now each node shows its top 8 text-similar semantic nodes that aren't
already neighbors, giving agents a search-like capability.
Also added section-level targeting guidance to linker.md, transfer.md,
and replay.md prompts: always target the most specific section, not
the file-level node.
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
Pattern separation for memory graph: when a file-level node (e.g.
identity.md) has section children, redistribute its links to the
best-matching section using cosine similarity.
- differentiate_hub: analyze hub, propose link redistribution
- refine_target: at link creation time, automatically target the
most specific section instead of the file-level hub
- Applied refine_target in all four link creation paths (digest
links, journal enrichment, apply consolidation, link-add command)
- Saturated hubs listed in agent topology header with "DO NOT LINK"
This prevents hub formation proactively (refine_target) and
remediates existing hubs (differentiate command).
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
- &PathBuf → &Path in memory-search.rs signatures
- Redundant field name in graph.rs struct init
- Add truncate(false) to lock file open
- Derive Default for Store instead of manual impl
- slice::from_ref instead of &[x.clone()]
- rsplit_once instead of split().last()
- str::repeat instead of iter::repeat().take().collect()
- is_none_or instead of map_or(true, ...)
- strip_prefix instead of manual slicing
Zero warnings on `cargo clippy`.
- Replace all 5 `Command::new("date")` calls across 4 files with
pure Rust time formatting via libc localtime_r
- Add format_date/format_datetime/format_datetime_space helpers to
capnp_store
- Move import_file, find_journal_node, export_to_markdown, render_file,
file_sections into Store methods where they belong
- Fix find_current_transcript to search all project dirs instead of
hardcoding bcachefs-tools path
- Fix double-reference .clone() warnings in cmd_trace
- Fix unused variable warning in neuro.rs
main.rs: 1290 → 1137 lines, zero warnings.
