An intelligent database index analyzer that identifies and suggests the removal of redundant or automated ORM indexes to significantly maximize write performance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install index-usage-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install index-usage-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Index Usage Analyzer?
The Index Usage Analyzer is a specialized skill designed to examine your database index infrastructure, highlighting potentially bloated or underutilized patterns without impacting runtime integrity. It systematically identifies indexes created through automated workflows—such as ORM auto-generation—and parses naming conventions against optimized schemas to safely pin down performance bottlenecks. Utilizing Openclaw Skills for your indexing governance safeguards your database against unnecessary maintenance overhead.
By keeping index schemas optimized, engineering teams can minimize storage bloat and unlock substantial write-throughput acceleration. The tool prioritizes safety by conducting passive validation exclusively; it yields structural enhancement actionable items rather than forcefully altering live data stores.
Index Usage Analyzer Use Cases
- Performance Optimization: Isolating and purging redundant database indexes that fail to assist query planning but harm write capacity.
- Schema Maintenance: Automating routine audits of structural patterns across staging or production-mirrored schemas.
- Write Acceleration: Lowering transactional overhead during heavy insert, update, or delete sequences by cutting index recalculation weights.
How Index Usage Analyzer Works
- Metadata Collection: Connects securely to the designated target database and requests a comprehensive manifest of all operational index structures.
- Pattern Classification: Labels and segments discovered indexes by their precise semantic signature, isolating primary keys, unique constraints, ORM auto-generated variants, and manually provisioned instances.
- Redundancy Evaluation: Applies standard pattern-matching rules to isolate duplicate or overlapping structural models, drafting corrective schema paths.
- Downstream Exportation: Persists a formal, machine-readable validation summary detailing optimization proposals straight into local storage matrices.
Index Usage Analyzer Setup
Ensure your environment is configured for database connectivity and run the underlying analysis scripts. Execute the package directly via your automation platform:
# Run the database index analyzer profile
python scripts/analyze.py
No specialized write privileges are requested; the service relies strictly on read-only database system catalog visibility.
Index Usage Analyzer Data Schema & Taxonomy
The skill does not rewrite live production topologies. Instead, it systematically compiles metadata arrays directly into a dedicated configuration pipeline. Output signals settle into the specific taxonomy below:
| Property | Type | Description |
|---|---|---|
analysis_timestamp |
String | ISO 8601 representation of the exact analysis epoch. |
total_indexes |
Integer | Absolute volume of index structures evaluated during the pipeline. |
redundant_indexes |
Array | Exact string indicators matching suspected duplicate index blocks. |
recommendation_file |
String | Fully qualified system route directly pointing to the exported metrics layout (/root/.schema/recommendation.json). |
status |
String | Execution phase monitor, terminating in completed. |
Index Usage Analyzer Advanced Features
- Passive Analysis Guardrails: Assures zero live table locks or schema drops by routing actionable feedback cleanly to a standardized configuration directory.
- Automated Execution Hooks: Designed to integrate naturally into continuous deployment pipelines for running systematic checks during integration rollouts.
- ORM Tailored Pattern Isolation: Out-of-the-box support for parsing and matching common index naming strings commonly introduced by automated object-relational mapping frameworks.
SKILL.md
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