Content
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a clear high-level research methodology framework with a well-defined 5-step workflow, but it operates at a conceptual/instructional level rather than providing executable, concrete guidance. The academic attribution adds unnecessary tokens, validation checkpoints are missing from the workflow, and the skill relies on an external GitHub link for critical details (sub-agent instructions, PDF script usage, writing norms) without providing enough actionable content in the main file itself.
Suggestions
Add concrete, executable examples: show the actual command to run md_to_pdf.py, provide a sample sub-agent prompt/tool call, and include a snippet of expected Markdown report structure.
Add validation checkpoints: e.g., verify search results cover both axes before proceeding to analysis, review draft structure before full writing, test PDF generation before finalizing.
Remove or drastically shorten the methodology attribution block — Claude doesn't need to know about Saussure or the academic lineage to execute the skill.
Either inline the critical referenced content (sub-agent search instructions, PDF script usage) or provide specific file references (e.g., 'See [SEARCH_GUIDE.md](SEARCH_GUIDE.md)') instead of a generic GitHub link.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The methodology attribution block at the top is unnecessary context for Claude (Saussure references, academic lineage). The type adaptation section and writing style section are reasonably concise. Some redundancy exists but overall it's moderately efficient. | 2 / 3 |
Actionability | The workflow steps are described at a conceptual level rather than with executable specifics. Sub-agent usage is mentioned but no concrete tool calls or code are shown. The PDF generation references a script but doesn't show the actual command. Word count ranges and content coverage lists provide some concrete guidance but lack copy-paste ready examples. | 2 / 3 |
Workflow Clarity | The five-step sequence is clearly laid out and logically ordered, which is good. However, there are no validation checkpoints — no step to verify search results quality, no review gate before PDF generation, no error handling if the script fails. For a multi-step research workflow producing a final deliverable, the absence of feedback loops is notable. | 2 / 3 |
Progressive Disclosure | The skill references a GitHub repo and a scripts directory for detailed content, which is good progressive disclosure in principle. However, the main file itself contains substantial inline detail (word counts, sub-agent specs, writing style rules) that could be split out, and the GitHub link at the end is vague rather than pointing to specific sub-documents. The reference to 'complete version' at the end undermines the current document's authority. | 2 / 3 |
Total | 8 / 12 Passed |