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.
git clone --depth 1 https://github.com/unixcrh/phuryn-pm-skillsWrote 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/commands/unixcrh/phuryn-pm-skills/write-query)<a href="https://agentmods.dev/commands/unixcrh/phuryn-pm-skills/write-query"><img src="https://agentmods.dev/badge/commands/unixcrh/phuryn-pm-skills/write-query/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/unixcrh/phuryn-pm-skills/write-query"><img src="https://agentmods.dev/badge/commands/unixcrh/phuryn-pm-skills/write-query.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00019 | $0.00622 |
| Opus 5.5 | $0.00008 | $0.00249 |
| Sonnet 5.5 | $0.00004 | $0.00124 |
| Haiku 4.5 | $0.00002 | $0.00062 |
Grade A, and why
write-query 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 1mo 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.
This is a copy
100% identical to write-query — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/write-query -- SQL Query Generator
Describe what data you need in plain English and get an optimized SQL query. Supports multiple dialects and can read your schema from uploaded files.
Invocation
/write-query Show me daily active users for the last 30 days, broken down by plan tier
/write-query Find users who signed up last month but never completed onboarding
/write-query [upload a schema diagram] What's the conversion rate from trial to paid by cohort?
Workflow
Step 1: Understand the Question
Parse the user's natural language request to identify:
- What data is being requested (metrics, dimensions, filters)
- Time range and granularity
- Grouping and ordering preferences
- Output expectations (raw data, aggregated, ranked)
Step 2: Determine Schema
If a schema is available (uploaded diagram, DDL, or description):
- Map the request to specific tables and columns
- Identify necessary joins
If no schema is provided:
- Ask for the database type (BigQuery, PostgreSQL, MySQL, etc.)
- Infer a reasonable schema from the question and ask the user to confirm
- Use common SaaS data model conventions as defaults
Step 3: Generate Query
Apply the sql-queries skill:
- Write the SQL query in the correct dialect
- Optimize for readability and performance
- Include comments explaining key logic
- Add CTEs for complex queries to improve readability
- Handle edge cases (NULLs, timezone considerations, duplicate handling)
Step 4: Present and Iterate
## SQL Query: [What It Does]
**Dialect**: [BigQuery / PostgreSQL / MySQL / etc.]
**Tables used**: [list]
### Query
[SQL code block with comments]
### What This Returns
[Description of the output: columns, rows, expected result shape]
### Assumptions
- [Schema assumptions made]
- [Business logic assumptions]
### Notes
- [Performance considerations for large datasets]
- [Edge cases handled or flagged]
Offer:
- "Want me to modify this — add filters, change grouping, extend the time range?"
- "Should I create a companion query for a related metric?"
- "Want me to build a dashboard around this query?"
- "Need a cohort analysis version of this?"
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.
- 1mo ago First seen · 85 lines · 19 tokens per session scan A ba8fb8e96238
write-query is a command published in the GitHub repository unixcrh/phuryn-pm-skills (2 stars, last pushed 7mo ago), licensed MIT. It adds 19 tokens to every session and 622 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to write-query, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
init
Initialize configurations for Supabase local development.
security
Scan a SQL string, .sql file, or SQL-building source file for injection risks with GoSQLX.
database-setup
Use when a project needs to store data and has no database yet. Setting up Supabase, creating tables, writing queries, and connecting them to the frontend. Written for designers.
new-migration
Scaffold a new database migration file pair (up + down) with auto-detection of migration tool and numbering.
json.batch_get
Read multiple JSON values by document and path.
json.batch_delete
Delete multiple JSON documents or paths in one itemwise batch.