ECC is a toolkit that organizes and improves how coding agents work through skills, memory, security checks, research practices, and related extensions. It is for developers using agents such as Claude Code, Codex, OpenCode, and Cursor.
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/affaan-m/ecc/postgres-patternsnpx skills add affaan-m/ECC --skill postgres-patternsgit clone --depth 1 https://github.com/affaan-m/ECCWrote 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/affaan-m/ecc/postgres-patterns)<a href="https://agentmods.dev/skills/affaan-m/ecc/postgres-patterns"><img src="https://agentmods.dev/badge/skills/affaan-m/ecc/postgres-patterns.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 | $0.00045 | $0.01090 |
| Opus 5 | $0.00023 | $0.00545 |
| Sonnet 5 | $0.00009 | $0.00218 |
| Haiku 4.5 | $0.00005 | $0.00109 |
Grade A, and why
postgres-patterns 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 yesterday.
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.
Copies of this mod
8 near-identical copies found in the catalogue:
- postgres-patterns — 100% identical, 0 lines differ
- postgres-patterns — 100% identical, 0 lines differ
- postgres-patterns — 100% identical, 2 lines differ
- postgres-patterns — 88% identical, 20 lines differ
- postgres-patterns — 88% identical, 20 lines differ
- postgres-patterns — 88% identical, 20 lines differ
- postgres-patterns — 83% identical, 17 lines differ
- postgres-patterns — 83% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Patterns
Quick reference for PostgreSQL best practices. For detailed guidance, use the database-reviewer agent.
When to Activate
- Writing SQL queries or migrations
- Designing database schemas
- Troubleshooting slow queries
- Implementing Row Level Security
- Setting up connection pooling
Quick Reference
Index Cheat Sheet
| Query Pattern | Index Type | Example |
|---|---|---|
WHERE col = value |
B-tree (default) | CREATE INDEX idx ON t (col) |
WHERE col > value |
B-tree | CREATE INDEX idx ON t (col) |
WHERE a = x AND b > y |
Composite | CREATE INDEX idx ON t (a, b) |
WHERE jsonb @> '{}' |
GIN | CREATE INDEX idx ON t USING gin (col) |
WHERE tsv @@ query |
GIN | CREATE INDEX idx ON t USING gin (col) |
| Time-series ranges | BRIN | CREATE INDEX idx ON t USING brin (col) |
Data Type Quick Reference
| Use Case | Correct Type | Avoid |
|---|---|---|
| IDs | bigint |
int, random UUID |
| Strings | text |
varchar(255) |
| Timestamps | timestamptz |
timestamp |
| Money | numeric(10,2) |
float |
| Flags | boolean |
varchar, int |
Common Patterns
Composite Index Order:
-- Equality columns first, then range columns
CREATE INDEX idx ON orders (status, created_at);
-- Works for: WHERE status = 'pending' AND created_at > '2024-01-01'
Covering Index:
CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Avoids table lookup for SELECT email, name, created_at
Partial Index:
CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Smaller index, only includes active users
RLS Policy (Optimized):
CREATE POLICY policy ON orders
USING ((SELECT auth.uid()) = user_id); -- Wrap in SELECT!
UPSERT:
INSERT INTO settings (user_id, key, value)
VALUES (123, 'theme', 'dark')
ON CONFLICT (user_id, key)
DO UPDATE SET value = EXCLUDED.value;
Cursor Pagination:
SELECT * FROM products WHERE id > $last_id ORDER BY id LIMIT 20;
-- O(1) vs OFFSET which is O(n)
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.
- yesterday First seen · 162 lines · 45 tokens per session scan A d8735f587443
postgres-patterns is a skill published in the GitHub repository affaan-m/ECC (248,541 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 1,090 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 2026-09-03.
Other skills, from other repositories
alembic-migration
Create, review, and apply database schema changes with Alembic. Use whenever a SQLAlchemy model is added or changed, a column/index/constraint needs to change, or a data backfill is required — anything that alters the PostgreSQL schema.
postgresql-table-design
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
postgres-expert
PostgreSQL expert for query optimization, indexing, extensions, and database administration.
sql-analyst
SQL query expert for optimization, schema design, and data analysis.
onboarding-milestones
Daily runbook for tracking new customer accounts against onboarding milestones in Postgres and HubSpot for {{projectName}}. Covers the milestone framework, stall and overdue detection, nudge drafting, the owning-CSM alert, and the human approval gate before anything sends or changes account state.
dsar-fulfillment
Daily GDPR data-subject-access-request runbook. Verifies each incoming request from Gmail, locates the subject's data read-only across every relevant Postgres table, compiles an access-or-deletion report in Google Docs within the {{sladays}}-day SLA, and flags it to {{legalreviewchannel}} for a lawyer to approve.…