Content
68%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-organized overview document with concrete quick-start commands and clean progressive-disclosure structure pointing to one-level-deep reference files. The main gaps are the absence of an inline validation/feedback checkpoint in the batch ingest workflow (capping workflow clarity at 3) and the fact that the referenced bundle files are not present in the skill directory as evaluated.
Suggestions
Add an explicit validation checkpoint to the ingest workflow (e.g., run `python scripts/lint_wiki.py` after the batch page updates, and verify index.md and log.md are consistent before finishing) so the 10-15-page batch write has a built-in feedback loop.
Merge 'Core principle' and 'Why this works (vs plain RAG)' into a single short section — both make the same compounding-vs-retrieval argument, and the table alone conveys it.
Ship the referenced bundle (references/, scripts/, assets/) with the skill, or inline the minimal ingest/query/lint steps in SKILL.md, so the workflow pointers resolve to real content even when the full bundle is absent.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and information-forward — tables of commands, agents, and scripts with one-line purposes, plus an actionable architecture diagram — with only minor trim opportunities: the 'Core principle' prose and the 'Why this works (vs plain RAG)' table restate the same compounding-vs-retrieval argument already in the description, and the 'Related skills' section is marginal. This matches 'Efficient; minor instances of over-explanation that could be trimmed' better than the level-3 anchor, since there is no padded tutorial-style explanation of concepts Claude already knows. | 4 / 5 |
Actionability | Quick start gives concrete, copy-paste-ready commands (`python scripts/init_vault.py --path ~/vaults/research --topic "LLM interpretability"`, `/wiki-ingest <path>`) and a concrete log-entry format (`## [YYYY-MM-DD] <op> | <title>`). It falls short of the level-5 'fully executable, specific examples cover the common cases' anchor because the actual ingest/query/lint mechanics live in reference files (not inline) and key details like the ingest discussion step and page-update conventions are only hinted at in the body. | 4 / 5 |
Workflow Clarity | The three core operations are clearly listed and the ingest sequence (read → discuss → write summary → update pages → update index → append log) is well-defined. However, ingest is a batch operation that writes/overwrites 10-15 wiki pages per run, and the body defines no inline validation checkpoint — the lint health-check is presented as a separate periodic operation rather than a post-ingest verification step. Per the rubric's cap, a batch/destructive workflow without validation cannot score above 3; this fits the level-3 anchor 'sequence present but checkpoints missing or implicit' rather than level 4. | 3 / 5 |
Progressive Disclosure | The body is structured as a clear overview with well-signaled, one-level-deep references — a dedicated 'Reference docs' section listing each file with a one-line purpose, plus a 'Python tools' table and an assets listing — matching 'Good structure; most content is appropriately placed; references mostly clear'. It stops short of level 5 because the bundle directories (references/, scripts/, assets/) are not present alongside SKILL.md, so the 11 referenced docs and 8 scripts cannot be verified to exist, and some overview sections (slash commands, sub-agents, Obsidian setup) could be consolidated into the reference files. | 4 / 5 |
Total | 15 / 20 Passed |