Content
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is well-structured and actionable with concrete paths and commands, but it lacks validation checkpoints in its workflows and references module files that are absent from the provided bundle.
Suggestions
Add an explicit validate/verify checkpoint to batch and append workflows (e.g., confirm a JSONL entry is well-formed after appending before proceeding).
Ensure referenced module files (identity/IDENTITY.md, content/CONTENT.md, network/NETWORK.md, operations/OPERATIONS.md, agents/AGENTS.md) exist in the bundle, or remove the broken references.
Trim the 'Integration' name-dropping and 'Skill Metadata' footer to reduce token overhead.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and mostly efficient, but the 'Integration' section name-drops context-engineering concepts and the 'Skill Metadata' footer adds filler that does not earn its tokens, so it could be tightened. | 2 / 3 |
Actionability | Workflows use concrete file paths (identity/voice.md, network/contacts.jsonl), a real executable command (python agents/scripts/weekly_review.py), and explicit pipelines (ideas.jsonl → drafts/ → posts.jsonl), giving copy-paste-ready guidance. | 3 / 3 |
Workflow Clarity | Multi-step workflows are clearly numbered and sequenced, but none include explicit validation or verification checkpoints for batch/append operations, which the rubric caps at 2. | 2 / 3 |
Progressive Disclosure | The L1/L2/L3 architecture is well signaled and a References section lists module docs, but the referenced paths (identity/IDENTITY.md, content/CONTENT.md, etc.) do not exist in the actual bundle, so navigation is partly broken. | 2 / 3 |
Total | 9 / 12 Passed |