home / skills / athola / claude-night-market / update-readme
This skill updates project READMEs with a structured, exemplar-aligned refresh that surfaces language-audit findings and governance notes.
npx playbooks add skill athola/claude-night-market --skill update-readmeReview the files below or copy the command above to add this skill to your agents.
---
name: update-readme
description: 'Run git-workspace-review first to capture repo context. Use when README
requires structural refresh, adding features to documentation, aligning readme with
exemplar standards, improving project presentation. Do not use when updating inline
docs - use doc-updates. DO NOT use when: consolidating ephemeral reports - use doc-consolidation.'
category: artifact-generation
tags:
- readme
- documentation
- exemplars
- research
- structure
tools:
- Read
- Write
- Edit
- Bash
- WebSearch
- TodoWrite
complexity: high
estimated_tokens: 1200
modules:
- language-audit
- exemplar-research
progressive_loading: true
dependencies:
- sanctum:shared
- sanctum:git-workspace-review
- imbue:evidence-logging
- scribe:slop-detector
- scribe:doc-generator
---
# README Update Workflow
## When To Use
Use this skill whenever the README requires a structural refresh.
Run `Skill(sanctum:git-workspace-review)` first to capture repo context and diffs.
## When NOT To Use
- Updating inline
docs - use doc-updates
- Consolidating ephemeral reports - use doc-consolidation
- Updating inline
docs - use doc-updates
- Consolidating ephemeral reports - use doc-consolidation
## Required TodoWrite Items
1. `update-readme:language-audit`
2. `update-readme:exemplar-research`
3. `update-readme:outline-aligned`
4. `update-readme:edits-applied`
5. `update-readme:slop-scanned` - AI marker detection via scribe
6. `update-readme:verification-reporting`
## Step 1 - Language Audit (`update-readme:language-audit`)
- Confirm `pwd`, `git status -sb`, and the baseline branch for reference.
- Detect dominant languages using repository heuristics (manifest files, file counts).
- Note secondary languages that influence documentation (e.g., a TypeScript frontend and a Rust backend) so the README can surface both.
- Record the method and findings.
See `modules/language-audit.md` for detailed detection patterns and commands.
## Step 2 - Exemplar Research (`update-readme:exemplar-research`)
- For each primary and secondary language, use web search to locate high-quality READMEs (star count, recency, maintainer activity).
- Capture 2-3 exemplar repositories per language and summarize why each is relevant (section order, visuals, quickstart clarity, governance messaging, math exposition, etc.).
- Store citations for every exemplar so the final summary references them explicitly.
See `modules/exemplar-research.md` for search query patterns and evaluation criteria.
## Step 3 - Outline Alignment (`update-readme:outline-aligned`)
- Compare current README headings (`rg -n '^#' README.md`) against patterns observed in exemplars.
- Draft a target outline covering: value proposition, installation, quickstart, deeper usage/configuration, architecture/feature highlights, performance or math guarantees, documentation links, contribution/governance, roadmap/status, and licensing/security notes.
- validate internal documents (docs/, specs/, wiki, commands/) are mapped to the relevant sections so the README anchors them with context-sensitive links.
## Step 4 - Apply Edits (`update-readme:edits-applied`)
- Implement the new structure directly in `README.md` (or the specified file).
- Maintain concise, evidence-based prose; avoid marketing fluff.
- Add comparison tables, feature lists, or diagrams only if they originate from current repository assets (no speculative content).
- When referencing algorithms or performance claims, point to benchmarks or tests within the repository or documented math reviews.
## Step 4.5 - AI Slop Detection (`update-readme:slop-scanned`)
Run `Skill(scribe:slop-detector)` on the updated README to detect AI-generated content markers.
### Scribe Integration
The scribe plugin provides AI slop detection:
```
Skill(scribe:slop-detector) --target README.md
```
This detects:
- **Tier 1 words**: delve, tapestry, comprehensive, leveraging, etc.
- **Phrase patterns**: "In today's fast-paced world", "cannot be overstated"
- **Structural markers**: Excessive em dashes, bullet overuse, sentence uniformity
- **Marketing language**: "enterprise-ready", "cutting-edge", "seamless"
### Remediation
If slop score exceeds 2.0 (moderate), apply `Skill(scribe:doc-generator)` principles:
1. Ground every claim with specifics
2. Remove formulaic openers/closers
3. Use numbers, commands, filenames over adjectives
4. Balance bullets with narrative prose
5. Show authorial perspective (trade-offs, reasoning)
For significant cleanup needs, use:
```
Agent(scribe:doc-editor) --target README.md
```
## Step 5 - Verification & Reporting (`update-readme:verification-reporting`)
- Re-read the updated README for clarity, accessibility (section lengths, bullet balance), and accurate links.
- Run `git diff README.md` (or the edited file) and capture snippets for the final report.
- Summarize detected languages, exemplar sources (with citations), key structural decisions, and follow-up TODOs (e.g., add badges, upload diagrams).
## Exit Criteria
- All `TodoWrite` items are complete.
- The README reflects a modern, language-aware structure, referencing both internal docs and external inspiration with citations.
- Research notes and command references are captured so future reviewers can reproduce the process.
## Troubleshooting
### Common Issues
**Documentation out of sync**
Run `make docs-update` to regenerate from code
**Build failures**
Check that all required dependencies are installed
**Links broken**
Verify relative paths in documentation files
This skill refreshes the project landing document structure and content to match exemplar standards and accurately surface features, installation, and governance. Run git-workspace-review first to capture workspace context and diffs before starting. It focuses on structural clarity, evidence-backed claims, and linking internal docs and tests.
The skill performs a language audit to detect dominant and secondary languages that should be surfaced. It gathers exemplar landing documents, drafts a target outline aligned with those exemplars, applies edits to the landing document, scans for AI-style language sloppiness, and produces a verification report with diffs and citations. Each step produces a TodoWrite item so progress and provenance are recorded.
Do I need to run any other skills before this one?
Yes — run git-workspace-review first to capture workspace context, branch, and diffs.
What if the landing document contains marketing language?
Use the slop detection step and remediate by grounding claims with specifics, removing formulaic openers, and adding links to tests or benchmarks.
When should I not use this skill?
Do not use it for inline code comments or ephemeral report consolidation; use a doc-updates or doc-consolidation flow instead.