Generates hierarchical AGENTS.md knowledge base files with complexity-scored subdirectory documentation.
Works with
Discovers project structure through parallel explore agents, bash analysis, LSP codemap, and existing documentation to build a complete codebase map
Scores directories by file count, code ratio, symbol density, and module boundaries to determine which subdirectories warrant their own AGENTS.md files
Generates root AGENTS.md with overview, structure, conventions, and anti-patterns,
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionindex-knowledgeExecute the skills CLI command in your project's root directory to begin installation:
Fetches index-knowledge from tursodatabase/turso 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 index-knowledge. Access via /index-knowledge 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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Generate hierarchical AGENTS.md files. Root + complexity-scored subdirectories.
--create-new # Read existing → remove all → regenerate from scratch
--max-depth=2 # Limit directory depth (default: 5)
Default: Update mode (modify existing + create new where warranted)
TodoWrite([
{ id: "discovery", content: "Fire explore agents + LSP codemap + read existing", status: "pending", priority: "high" },
{ id: "scoring", content: "Score directories, determine locations", status: "pending", priority: "high" },
{ id: "generate", content: "Generate AGENTS.md files (root + subdirs)", status: "pending", priority: "high" },
{ id: "review", content: "Deduplicate, validate, trim", status: "pending", priority: "medium" }
])
Mark "discovery" as in_progress.
Multiple Task calls in a single message execute in parallel. Results return directly.
// All Task calls in ONE message = parallel execution
Task(
description="project structure",
subagent_type="explore",
prompt="Project structure: PREDICT standard patterns for detected language → REPORT deviations only"
)
Task(
description="entry points",
subagent_type="explore",
prompt="Entry points: FIND main files → REPORT non-standard organization"
)
Task(
description="conventions",
subagent_type="explore",
prompt="Conventions: FIND config files (.eslintrc, pyproject.toml, .editorconfig) → REPORT project-specific rules"
)
Task(
description="anti-patterns",
subagent_type="explore",
prompt="Anti-patterns: FIND 'DO NOT', 'NEVER', 'ALWAYS', 'DEPRECATED' comments → LIST forbidden patterns"
)
Task(
description="build/ci",
subagent_type="explore",
prompt="Build/CI: FIND .github/workflows, Makefile → REPORT non-standard patterns"
)
Task(
description="test patterns",
subagent_type="explore",
prompt="Test patterns: FIND test configs, test structure → REPORT unique conventions"
)
| Factor | Threshold | Additional Agents |
|---|---|---|
| Total files | >100 | +1 per 100 files |
| Total lines | >10k | +1 per 10k lines |
| Directory depth | ≥4 | +2 for deep exploration |
| Large files (>500 lines) | >10 files | +1 for complexity hotspots |
| Monorepo | detected | +1 per package/workspace |
| Multiple languages | >1 | +1 per language |
# Measure project scale first
total_files=$(find . -type f -not -path '*/node_modules/*' -not -path '*/.git/*' | wc -l)
total_lines=$(find . -type f \( -name "*.ts" -o -name "*.py" -o -name "*.go" \) -not -path '*/node_modules/*' -exec wc -l {} + 2>/dev/null | tail -1 | awk '{print $1}')
large_files=$(find . -type f \( -name "*.ts" -o -name "*.py" \) -not -path '*/node_modules/*' -exec wc -l {} + 2>/dev/null | awk '$1 > 500 {count++} END {print count+0}')
max_depth=$(find . -type d -not -path '*/node_modules/*' -not -path '*/.git/*' | awk -F/ '{print NF}' | sort -rn | head -1)
Example spawning (all in ONE message for parallel execution):
// 500 files, 50k lines, depth 6, 15 large files → spawn additional agents
Task(
description="large files",
subagent_type="explore",
prompt="Large file analysis: FIND files >500 lines, REPORT complexity hotspots"
)
Task(
description="deep modules",
subagent_type="explore",
prompt="Deep modules at depth 4+: FIND hidden patterns, internal conventions"
)
Task(
description="cross-cutting",
subagent_type="explore",
prompt="Cross-cutting concerns: FIND shared utilities across directories"
)
// ... more based on calculation
While Task agents execute, main session does:
# Directory depth + file counts
find . -type d -not -path '*/\.*' -not -path '*/node_modules/*' -not -path '*/venv/*' -not -path '*/dist/*' -not -path '*/build/*' | awk -F/ '{print NF-1}' | sort -n | uniq -c
# Files per directory (top 30)
find . -type f -not -path '*/\.*' -not -path '*/node_modules/*' | sed 's|/[^/]*$||' | sort | uniq -c | sort -rn | head -30
# Code concentration by extension
find . -type f \( -name "*.py" -o -name "*.ts" -o -name "*.tsx" -o -name "*.js" -o -name "*.go" -o -name "*.rs" \) -not -path '*/node_modules/*' | sed 's|/[^/]*$||' | sort | uniq -c | sort -rn | head -20
# Existing AGENTS.md / CLAUDE.md
find . -type f \( -name "AGENTS.md" -o -name "CLAUDE.md" \) -not -path '*/node_modules/*' 2>/dev/null
For each existing file found:
Read(filePath=file)
Extract: key insights, conventions, anti-patterns
Store in EXISTING_AGENTS map
If --create-new: Read all existing first (preserve context) → then delete all → regenerate.
lsp_servers() # Check availability
# Entry points (parallel)
lsp_document_symbols(filePath="src/index.ts")
lsp_document_symbols(filePath="main.py")
# Key symbols (parallel)
lsp_workspace_symbols(filePath=".", query="class")
lsp_workspace_symbols(filePath=".", query="interface")
lsp_workspace_symbols(filePath=".", query="function")
# Centrality for top exports
lsp_find_references(filePath="...", line=X, character=Y)
LSP Fallback: If unavailable, rely on explore agents + AST-grep.
Merge: bash + LSP + existing + Task agent results. Mark "discovery" as completed.
Mark "scoring" as in_progress.
| Factor | Weight | High Threshold | Source |
|---|---|---|---|
| File count | 3x | >20 | bash |
| Subdir count | 2x | >5 | bash |
| Code ratio | 2x | >70% | bash |
| Unique patterns | 1x | Has own config | explore |
| Module boundary | 2x | Has index.ts/init.py | bash |
| Symbol density | 2x | >30 symbols | LSP |
| Export count | 2x | >10 exports | LSP |
| Reference centrality | 3x | >20 refs | LSP |
| Score | Action |
|---|---|
| Root (.) | ALWAYS create |
| >15 | Create AGENTS.md |
| 8-15 | Create if distinct domain |
| <8 | Skip (parent covers) |
AGENTS_LOCATIONS = [
{ path: ".", type: "root" },
{ path: "src/hooks", score: 18, reason: "high complexity" },
{ path: "src/api", score: 12, reason: "distinct domain" }
]
Mark "scoring" as completed.
Mark "generate" as in_progress.
# PROJECT KNOWLEDGE BASE
**Generated:** {TIMESTAMP}
**Commit:** {SHORT_SHA}
**Branch:** {BRANCH}
## OVERVIEW
{1-2 sentences: what + core stack}
## STRUCTURE
\`\`\`
{root}/
├── {dir}/ # {non-obvious purpose only}
└── {entry}
\`\`\`
## WHERE TO LOOK
| Task | Location | Notes |
|------|----------|-------|
## CODE MAP
{From LSP - skip if unavailable or project <10 files}
| Symbol | Type | Location | Refs | Role |
## CONVENTIONS
{ONLY deviations from standard}
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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
index-knowledge is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: index-knowledge is focused, and the summary matches what you get after install.
index-knowledge fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: index-knowledge is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: index-knowledge is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: index-knowledge is focused, and the summary matches what you get after install.
index-knowledge is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for index-knowledge matched our evaluation — installs cleanly and behaves as described in the markdown.
index-knowledge has been reliable in day-to-day use. Documentation quality is above average for community skills.
index-knowledge reduced setup friction for our internal harness; good balance of opinion and flexibility.
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