Agentic Plugin Marketplace is a collection of reusable plugins, agents, skills, commands, and rules for coding-agent tools including Claude Code, Codex CLI, Cursor, OpenCode, Antigravity CLI, and GitHub Copilot. It is for developers assembling agentic workflows across multiple harnesses from shared Markdown sources, and the catalogue entries are examples or subsets of those workflow components.
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 skills add wshobson/agents --skill postgresql-table-designgit clone --depth 1 https://github.com/wshobson/agentsWrote 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/wshobson/agents/postgresql-table-design)<a href="https://agentmods.dev/skills/wshobson/agents/postgresql-table-design"><img src="https://agentmods.dev/badge/skills/wshobson/agents/postgresql-table-design/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/skills/wshobson/agents/postgresql-table-design"><img src="https://agentmods.dev/badge/skills/wshobson/agents/postgresql-table-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Output Handling · line 32 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
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 | $0.00037 | $0.01983 |
| Opus 5.5 | $0.00015 | $0.00793 |
| Sonnet 5.5 | $0.00007 | $0.00397 |
| Haiku 4.5 | $0.00004 | $0.00198 |
Grade A, and why
postgresql-table-design 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Table Design
When to Use
- Designing a new PostgreSQL schema, or reviewing one before it ships.
- Choosing column types, keys, constraints, or indexes for PostgreSQL specifically.
- Deciding whether and how to partition a large table, or how to store semi-structured data.
- Planning a schema change on a live database without downtime.
The rules and decision points for a PostgreSQL schema. The full data-type catalog, workload
patterns (update-heavy, insert-heavy, upsert, schema evolution), extensions, JSONB indexing,
and worked DDL examples are in references/details.md; open it when a section below points there.
Core Rules
- Define a PRIMARY KEY for reference tables (users, orders, etc.). Not always needed for time-series/event/log data. When used, prefer
BIGINT GENERATED ALWAYS AS IDENTITY; useUUIDonly when global uniqueness/opacity is needed. - Normalize first (to 3NF) to eliminate data redundancy and update anomalies; denormalize only for measured, high-ROI reads where join performance is proven problematic.
- Add NOT NULL everywhere it is semantically required; use DEFAULTs for common values.
- Create indexes for access paths you actually query: PK/unique (auto), FK columns (manual!), frequent filters/sorts, and join keys.
- Prefer TIMESTAMPTZ for event time; NUMERIC for money; TEXT for strings; BIGINT for integers; DOUBLE PRECISION for floats (or
NUMERICfor exact decimal arithmetic).
PostgreSQL Gotchas
- Identifiers: unquoted → lowercased. Avoid quoted/mixed-case names; use
snake_case. - Unique + NULLs: UNIQUE allows multiple NULLs. Use
UNIQUE NULLS NOT DISTINCT (...)(PG15+) to restrict to one NULL. - FK indexes: PostgreSQL does not auto-index FK columns. Add them.
- No silent coercions: length/precision overflows error out (no truncation). Inserting 999 into
NUMERIC(2,0)fails, unlike databases that silently truncate or round. - Sequences/identity have gaps (normal; don't "fix"). Rollbacks, crashes, and concurrent transactions leave gaps (1, 2, 5, 6...).
- Heap storage: no clustered PK by default;
CLUSTERis a one-off reorganization, not maintained on later inserts. - MVCC: updates/deletes leave dead tuples; vacuum handles them—design to avoid hot wide-row churn.
What ships with it
1 file 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.
- 1mo ago First seen · 130 lines · 37 tokens per session scan A 1e27b0fac6d8
postgresql-table-design is a skill published in the GitHub repository wshobson/agents (41,158 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,983 once invoked, about $0.0001 per session on Opus 5.5. 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
data-sql-optimization
Diagnoses and tunes SQL for OLTP workloads on PostgreSQL, MySQL, and SQL Server. Use when tuning queries, reading plans, indexing, or fixing lock contention.
software-database-design
Designs database schemas, migrations, and data models for PostgreSQL, MySQL, MongoDB, and Redis. Use when planning tables, relationships, indexes, or ORM-backed schema changes.
ai-vector-brain
Creates reusable vector-brain implementations: repo, docs, compliance. Use when building pgvector SQL, manifests, ingest scripts. Not for context design (dev-context-engineering).
dev-supabase
Backend development with Supabase. Trigger when the user wants to configure auth, the database, or Supabase storage.
ops-database
Database schema design. Trigger when the user wants to create tables, migrations, or optimize queries.
postgres-patterns
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Quick reference for common patterns, index types, data types, and anti-pattern detection. Based on Supabase best practices.