Content
82%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 high-quality operational skill: executable SQL/bash at every step, a sensible highest-value-first ingestion order, privacy and provenance guidance, and correct use of a one-level reference file for the event schema. The main weaknesses are repeated checkpoint-schema details across sections and the absence of an explicit validation pass over the generated wiki pages before manifest update.
Suggestions
State the checkpoint JSON fields (title, overview, work_done, technical_details, important_files, next_steps) once — in the data-layout section — and reference that list from 'Key data sources' and Step 2 instead of repeating it three times.
Add an explicit validation checkpoint between Step 5 and Step 6: verify each created/updated page exists, has the required summary/confidence/lifecycle frontmatter, and is linked from its project overview before updating .manifest.json.
Consolidate the survey SQL (data-layout section) and the Step 1/Step 2 queries into one place, keeping only the delta-classification logic in Step 1 to reduce duplicated query text.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Overall lean and dense — tables, SQL, and directory trees instead of prose, and no explanation of concepts Claude already knows. However, there is repeated content: the checkpoint fields (title, overview, work_done, technical_details, important_files, next_steps) appear three times (source layout, ranked data sources, Step 2), and the survey/aggregation SQL overlaps between the data-layout section and Steps 1–3. This fits the 4 anchor ("minor instances of over-explanation that could be trimmed") better than 3, since the redundancy is duplication rather than unnecessary teaching. | 4 / 5 |
Actionability | Fully executable throughout: copy-paste-ready SQL for every session-store table, bash survey commands, a Python base64 decode snippet, the exact obsidian-wiki memory sync invocation with flags, a concrete manifest JSON schema, and a decision table mapping content type to vault location. Matches the 5 anchor — code/commands cover the common cases end to end. | 5 / 5 |
Workflow Clarity | Clear numbered sequence (survey/delta → checkpoints first → turns → memory artifacts → patterns → cluster → distill → manifest/journal) with meaningful checkpoints: manifest-based delta classification with an explicit user-facing report ("Found X sessions... Delta: B new, C modified") and a QMD refresh section with failure handling ("If QMD refresh fails, do not roll back the vault changes; report the QMD status separately"). Because this is a batch operation and validation is present (delta reporting, QMD verify, manifest guard), the batch cap at 3 does not apply — but there is no explicit validation of the written wiki pages themselves, which keeps it at the 4 anchor ("clear sequence with most checkpoints present; minor validation gaps") rather than 5. | 4 / 5 |
Progressive Disclosure | Good structure with a real, verified one-level-deep reference: the event-JSONL schema is deferred to references/copilot-data-format.md (confirmed present in the bundle), signaled both at Step 3 and in a Reference section. Cross-skill pointers (llm-wiki/SKILL.md, MEMORY.md) are named by section, which aids navigation. It falls short of the 5 anchor because the body still inlines substantial data-layout documentation (full directory trees and per-table schemas) that could partly live in the reference file, leaving minor organization gaps — squarely the 4 anchor. | 4 / 5 |
Total | 17 / 20 Passed |