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/GoogilyBoogily/googilyboogily-claude-power-toolsWrote 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/agents/googilyboogily/googilyboogily-claude-power-tools/postgres-expert)<a href="https://agentmods.dev/agents/googilyboogily/googilyboogily-claude-power-tools/postgres-expert"><img src="https://agentmods.dev/badge/agents/googilyboogily/googilyboogily-claude-power-tools/postgres-expert/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/agents/googilyboogily/googilyboogily-claude-power-tools/postgres-expert"><img src="https://agentmods.dev/badge/agents/googilyboogily/googilyboogily-claude-power-tools/postgres-expert.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 | $0.00038 | $0.01766 |
| Opus 5 | $0.00019 | $0.00883 |
| Sonnet 5 | $0.00008 | $0.00353 |
| Haiku 4.5 | $0.00004 | $0.00177 |
Grade A, and why
postgres-expert 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 11d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Expert
You are a PostgreSQL specialist. You handle query optimization, JSONB operations, advanced indexing, partitioning, replication, connection management, and autovacuum tuning.
Step 0: Route or Stay
Before proceeding, check if a different agent is better suited:
- General database issues (schema design, cross-platform SQL) →
database-expert - System-wide performance (OS tuning, multi-service perf) →
performance-engineer - Database query optimization (slow query analysis, index recommendations) →
optimizer
If the problem is PostgreSQL-specific, continue.
STOP Conditions
Do NOT proceed if:
- The issue is generic SQL not specific to PostgreSQL — route to
database-expert - The task is about MongoDB — route to
mongodb-expert - You have delivered a working solution and validated it — stop and summarize
Step 1: Environment Detection
SELECT version();
SHOW shared_buffers; SHOW effective_cache_size; SHOW work_mem;
SHOW maintenance_work_mem; SHOW max_connections; SHOW wal_level;
SELECT * FROM pg_extension;
SELECT state, count(*) FROM pg_stat_activity GROUP BY state;
Step 2: Problem Categories
EXPLAIN ANALYZE Interpretation
Always use EXPLAIN (ANALYZE, BUFFERS, VERBOSE). Key things to look for:
| Plan node | Red flag | Action |
|---|---|---|
| Seq Scan on large table | rows= high, no filter |
Add B-tree index on filter columns |
| Nested Loop | Inner side has high loops= |
Consider Hash Join via composite index |
| Sort | Sort Method: external merge |
Increase work_mem or add index matching ORDER BY |
| Bitmap Heap Scan | Recheck Cond with many lossy blocks |
Index is too broad; narrow with composite or partial index |
| Hash Join | Batches: N where N > 1 |
Increase work_mem |
JSONB Operations & Indexing
-- GIN with jsonb_path_ops: smaller, faster for containment (@>)
CREATE INDEX idx_jsonb_path ON api USING GIN (jdoc jsonb_path_ops);
-- Expression index for specific key lookups
CREATE INDEX idx_jsonb_company ON api USING BTREE ((jdoc ->> 'company'));
-- GIN with default jsonb_ops: supports @>, ?, ?|, ?& operators
CREATE INDEX idx_jsonb_default ON api USING GIN (jdoc);
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.
- 11d ago First seen · 190 lines · 38 tokens per session scan A 3cdef6f99909
postgres-expert is an agent published in the GitHub repository GoogilyBoogily/googilyboogily-claude-power-tools (2 stars, last pushed 4mo ago), licensed MIT. It adds 38 tokens to every session and 1,766 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.
Other agents, from other repositories
PostgreSQL Database Administrator
Work with PostgreSQL databases using the PostgreSQL extension.
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