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/clidey/whodb/query-buildernpx skills add clidey/whodb --skill query-buildergit clone --depth 1 https://github.com/clidey/whodbWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/clidey/whodb/query-builder)<a href="https://agentmods.dev/skills/clidey/whodb/query-builder"><img src="https://agentmods.dev/badge/skills/clidey/whodb/query-builder.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00040 | $0.00892 |
| Opus 5 | $0.00020 | $0.00446 |
| Sonnet 5 | $0.00008 | $0.00178 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
query-builder 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 4d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Query Builder
Convert natural language questions into SQL queries using the database schema.
When to Use
Activate when user asks questions like:
- "Show me all users who signed up last month"
- "Find orders greater than $100"
- "Which products have low inventory?"
- "Get the top 10 customers by total spend"
Workflow
1. Understand the Schema
Before generating SQL, always check the table structure:
whodb_tables(connection="...") → Get available tables
whodb_columns(table="relevant_table") → Get column names and types
2. Identify Intent
Parse the natural language request:
- Subject: What entity? (users, orders, products)
- Filter: What conditions? (last month, > $100, active)
- Aggregation: Count, sum, average, max, min?
- Grouping: By what dimension?
- Ordering: Sort by what? Ascending/descending?
- Limit: How many results?
3. Map to Schema
- Match entities to table names
- Match attributes to column names
- Identify foreign key joins needed
4. Generate SQL
Build the query following SQL best practices:
SELECT columns
FROM table
[JOIN other_table ON condition]
WHERE filters
[GROUP BY columns]
[HAVING aggregate_condition]
ORDER BY column [ASC|DESC]
LIMIT n;
5. Execute and Present
whodb_query(query="generated SQL")
Translation Patterns
| Natural Language | SQL Pattern |
|---|---|
| "last week/month/year" | WHERE date_col >= DATE_SUB(NOW(), INTERVAL 1 WEEK) |
| "more than X" / "greater than X" | WHERE col > X |
| "top N" | ORDER BY col DESC LIMIT N |
| "how many" | SELECT COUNT(*) |
| "total" / "sum of" | SELECT SUM(col) |
| "average" | SELECT AVG(col) |
| "for each" / "by" | GROUP BY col |
| "between X and Y" | WHERE col BETWEEN X AND Y |
| "contains" / "like" | WHERE col LIKE '%term%' |
| "starts with" | WHERE col LIKE 'term%' |
| "is empty" / "is null" | WHERE col IS NULL |
| "is not empty" | WHERE col IS NOT NULL |
Date Handling by Database
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.
- 4d ago First seen · 131 lines · 40 tokens per session scan A 747b7b9166a3
query-builder is a skill published in the GitHub repository clidey/whodb (5,018 stars, last pushed today), licensed Apache-2.0. It adds 40 tokens to every session and 892 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 2026-08-30.
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