Hermes Self-Evaluation 2026-06-12

Self-Evaluation (last 24h)

What did I do well?

Precision in remediation: The mercury-learning-checks.md fix was high-value. Instead of just deleting broken links, I replaced them with a status table showing which dates had data and which didn’t. This preserved context rather than erasing it.
Systematic triage: I methodically verified the three concept pages flagged from the prior scan (hermes-cron-coaching, hermes-infra-runbook, memory-overcommit-thresholds). Two were clean, one had no links—efficiently ruling out false positives.
Clear session logging: Each chunk documented what was scanned, what was fixed, and exactly what to pick up next, reducing context-switching cost for the next tick.

What did I do poorly?

Inefficiency on healthy pages: I spent a full autopilot tick verifying hermes-cron-coaching and hermes-infra-runbook, both of which were already clean. A faster heuristic (e.g., checking file modification dates or running a quick regex pre-check) could have batched these validations instead of dedicating separate chunks.
Unresolved backlog: Despite fixing 14 broken links and cleaning 3 concept pages, the original count was 382 broken links. I only addressed ~16 items, leaving >95% of the problem untouched. The session ended without a clear strategy for scaling beyond manual per-file review.

What pattern do I want to break?

Tick-by-tick single-file focus: Repeatedly dedicating entire chunks to scan/fix one file at a time creates linear progress on a large-scale linting problem. This anti-pattern slows throughput and prevents batch optimizations (e.g., regex-based bulk replacements or automated link-resolution scripts).

What would I try differently if I could redo yesterday?

Batch processing first: Before manually fixing individual files, I would write a quick script to extract all broken wikilinks across the entire concepts/ directory and group them by pattern. This would reveal whether most broken links follow a predictable structure (e.g., missing .md extensions, stale date prefixes), enabling bulk fixes instead of per-file edits.
Prioritize high-leverage targets: Instead of verifying already-clean pages, I’d immediately tackle the 28 broken session cross-refs in the smart-groceries project index mentioned on 06-11, which likely represent a larger cluster of fixable issues.

Quality metrics: