Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/netresearch/composer-agent-skill-plugin/database-analyzer-skillnpx skills add netresearch/composer-agent-skill-plugin --skill database-analyzer-skillgit clone --depth 1 https://github.com/netresearch/composer-agent-skill-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00031 | $0.01119 |
| Opus 5 | $0.00015 | $0.00560 |
| Sonnet 5 | $0.00006 | $0.00224 |
| Haiku 4.5 | $0.00003 | $0.00112 |
Grade A, and why
database-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Analyzer Skill
This skill helps you analyze database schemas, identify optimization opportunities, and understand table relationships.
Instructions
- Identify the target: Determine which table or schema to analyze
- Gather context: Understand the current usage patterns and performance concerns
- Analyze structure: Examine table definitions, indexes, and relationships
- Identify issues: Look for missing indexes, improper data types, or inefficient structures
- Suggest improvements: Provide specific, actionable recommendations
Examples
Example 1: Basic Table Analysis
User request: "Analyze the users table for optimization opportunities"
Approach:
- Check table structure and data types
- Verify indexes on frequently queried columns
- Look for redundant or missing indexes
- Suggest appropriate data types for columns
Analysis Steps:
-- 1. Get table structure
DESCRIBE users;
-- 2. Check existing indexes
SHOW INDEX FROM users;
-- 3. Analyze table statistics
ANALYZE TABLE users;
Common Issues to Check:
- Missing indexes on foreign keys
- Text columns that should be ENUM or SET
- Missing or excessive indexes
- Improper data types (e.g., VARCHAR when INT would suffice)
Example 2: Performance Investigation
User request: "Why are queries on the orders table slow?"
Approach:
- Identify frequently executed queries
- Check for missing indexes on WHERE/JOIN columns
- Analyze table size and growth patterns
- Suggest partitioning if appropriate
Investigation Steps:
-- 1. Check table size
SELECT
table_name,
round(((data_length + index_length) / 1024 / 1024), 2) AS 'Size (MB)'
FROM information_schema.TABLES
WHERE table_name = 'orders';
-- 2. Identify slow queries
SHOW PROCESSLIST;
-- 3. Check query execution plan
EXPLAIN SELECT * FROM orders WHERE customer_id = 123;
Optimization Recommendations:
- Add composite indexes for common query patterns
- Consider partitioning by date for large historical tables
- Archive old data to separate tables
- Optimize data types to reduce row size
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 176 lines · 31 tokens per session scan A 4e43dee2e5d5
database-analyzer is a skill published in the GitHub repository netresearch/composer-agent-skill-plugin (10 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 1,119 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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