| name | fullcheck |
| description | Comprehensive writing review — spawns analyser agents for thorough quality and voice assessment. Use when the user asks for a "full check", "thorough review", "comprehensive edit", or wants detailed quality analysis of their writing. |
| argument-hint | [file/dir/text] |
| disable-model-invocation | true |
/fullcheck — Comprehensive Writing Review
Thorough quality review using writing-analyser subagents. Use this for important documents that need a proper edit.
Determine Input
Figure out what to check:
- File path(s) passed as arguments → use those files
- Directory path → use the files in it (markdown/text files)
- Inline text → use it directly
- Nothing passed → look at recent conversation context for text being discussed. If genuinely unclear, ask the user what they'd like checked.
Spawn Analyser Agents
Launch writing-analyser subagents in parallel using the Task tool. Split the work sensibly:
For a single document:
- Agent 1: Focus on nonos.md compliance and general writing quality (slop, clarity, word choice, rhythm)
- Agent 2: Focus on Danny's voice, structure, and overall effectiveness (voice compliance, structural patterns, document flow)
For multiple documents:
- One agent per document (up to 3-4), each doing a full review
Give each agent clear instructions about what to focus on and pass the file path(s) or text.
Compile Results
Once the agents return, compile their reports into a single comprehensive review:
- Deduplicate — if both agents flag the same issue, list it once
- Prioritise — order by severity (critical → warnings → suggestions)
- Summarise — add a brief overall assessment at the top
Output Format
## Overall Assessment
[2-3 sentences: what's the text doing well, what needs the most work]
## Critical Issues
[Must fix — slop, errors, broken clarity]
## Warnings
[Should fix — weak language, structural problems, voice misses]
## Suggestions
[Nice to have — polish, enhancement opportunities]
## CLI Tool Output
[If agents ran write-good/proselint, include notable findings here]
Keep the compiled report concise and actionable. The user wants to know what to fix, not read an essay about their essay.
