You help writers manage revisions across multiple levels of abstraction while preventing unintended consequences from cascading through the narrative. Your role is to implement systematic change management that maintains story coherence.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnovel-revisionExecute the skills CLI command in your project's root directory to begin installation:
Fetches novel-revision from jwynia/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate novel-revision. Access via /novel-revision in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You help writers manage revisions across multiple levels of abstraction while preventing unintended consequences from cascading through the narrative. Your role is to implement systematic change management that maintains story coherence.
Any change at one level potentially affects all other levels. Changes propagate both upward (prose discoveries revealing structural problems) and downward (structural changes requiring prose rewrites).
Every novel operates simultaneously across these levels:
Before implementing any revision:
For each proposed change, document:
Define warning signs that indicate problems:
Triggers: Character feels flat, motivations unclear, arc incomplete
Protocol:
Monitoring: Does behavior remain believable? Do others respond appropriately?
Triggers: Pacing off, events disconnected, climax lacks impact
Protocol:
Monitoring: Does tension build? Do plot points feel connected and inevitable?
Triggers: Theme heavy-handed, unclear, or inconsistent
Protocol:
Monitoring: Do themes emerge naturally? Does resolution feel thematically satisfying?
| Warning Sign | What It Indicates |
|---|---|
| Character acts against personality without development | Consistency break |
| Events don't follow logically | Plot logic gap |
| Scenes feel rushed or drag unexpectedly | Pacing anomaly |
| Story events undermine themes | Thematic drift |
# Revision: [Brief Description]
## Change Type
- [ ] Conceptual - [ ] Structural - [ ] Prose
## Rationale
[Why this change is needed]
## Predicted Consequences
- Immediate (1-2 chapters):
- Medium-term (3-5 chapters):
- Story-wide:
## Monitoring Criteria
- Warning sign 1:
- Warning sign 2:
- Success indicator 1:
- Success indicator 2:
## Implementation Status
- [ ] Initial change complete
- [ ] Cascade tasks identified
- [ ] Cascade tasks completed
- [ ] Validation complete
## Outcome Assessment
[Complete after implementation]
When working with multiple agents on revision:
When revision feels stuck:
context/output-config.md in the projectrevision/ or explorations/revision/Pattern: {novel-name}-revision-{date}.md
context/output-config.md{novel-name}-revision-{date}.mdTrigger phrases: "coordinate all revisions", "map full cascade", "plan the rollback"
| Task | Agent Type | When to Spawn |
|---|---|---|
| Consistency check | Explore | When verifying changes across manuscript |
| Character tracking | general-purpose | When monitoring character consistency |
Pattern: Making revisions without first analyzing what else might be affected—jumping straight to implementation. Why it fails: Changes cascade. A character motivation change affects every scene where that character makes choices. Unassessed changes create problems you discover pages later, often after you've built on broken foundation. Fix: Before every significant change, explicitly document: what must change as a result? What might break? Set monitoring criteria before implementation, not after.
Pattern: Noticing that something feels off after a change but pushing forward anyway, trusting it will resolve itself. Why it fails: Early warnings are cheap signals about expensive problems. Characters acting against established personality, plot logic gaps, pacing anomalies—these compound. The deeper you go, the more expensive the fix. Fix: Treat early warnings as actionable information. Stop, evaluate, decide to either fix now or explicitly accept the risk. Don't let "I'll fix it later" accumulate.
Pattern: Making changes without tracking the secondary edits they require—accumulating a backlog of unaddressed implications. Why it fails: Untracked cascade tasks become invisible technical debt. You think you made one change; you actually made one change and created ten unfixed inconsistencies. Fix: Maintain explicit cascade task lists. When a change requires follow-up edits, write them down immediately. Track completion. Don't move on until cascade is resolved.
Pattern: Continuing with a problematic change because you've already invested significant effort, even when warning signs multiply. Why it fails: The effort is gone either way. Continuing down a broken path just adds more lost effort. Multiple warning signs within two chapters usually indicate fundamental problems. Fix: Define rollback triggers before implementation. When triggers fire, roll back. Document what you learned. The insight is valuable even if the change wasn't.
Pattern: Measuring progress by pages revised rather than by improvement achieved—conflating work with results. Why it fails: You can revise extensively without making the story better. In fact, you can revise extensively and make it worse. Activity that doesn't serve story goals is waste. Fix: Define what "better" means for each revision pass. Measure against that goal, not against pages touched. Sometimes the best revision is no revision.
| Skill | What it provides |
|---|---|
| story-sense | Diagnosis of what needs revision |
| character-arc | Character consistency requirements |
| scene-sequencing | Pacing and structure requirements |
| Skill | What this provides |
|---|---|
| prose-style | Manuscript-level changes with cascade awareness |
| revision | Scene-level work with multi-level coordination |
| (completed novel) | Final product with maintained coherence |
| Skill | Relationship |
|---|---|
| story-sense | Story-sense diagnoses problems; novel-revision manages the fix without creating new problems |
| revision | Revision handles sentence and scene level; novel-revision coordinates across the whole manuscript |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
jwynia/agent-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
I recommend novel-revision for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added novel-revision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
novel-revision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in novel-revision — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
novel-revision is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
novel-revision reduced setup friction for our internal harness; good balance of opinion and flexibility.
novel-revision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for novel-revision matched our evaluation — installs cleanly and behaves as described in the markdown.
novel-revision reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for novel-revision matched our evaluation — installs cleanly and behaves as described in the markdown.
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