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 fmflurry/settings-opencode --skill postgres-performance-tuninggit clone --depth 1 https://github.com/fmflurry/settings-opencodeWrote 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/fmflurry/settings-opencode/postgres-performance-tuning)<a href="https://agentmods.dev/skills/fmflurry/settings-opencode/postgres-performance-tuning"><img src="https://agentmods.dev/badge/skills/fmflurry/settings-opencode/postgres-performance-tuning/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/fmflurry/settings-opencode/postgres-performance-tuning"><img src="https://agentmods.dev/badge/skills/fmflurry/settings-opencode/postgres-performance-tuning.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 | $0.00160 | $0.02720 |
| Opus 5.5 | $0.00064 | $0.01088 |
| Sonnet 5.5 | $0.00032 | $0.00544 |
| Haiku 4.5 | $0.00016 | $0.00272 |
Grade A, and why
postgres-performance-tuning 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 27d 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Performance Tuning
Target version: postgres:16-alpine — this repository's gc-platform-postgres container: mem_limit: 1g, mem_reservation: 512m, no command: override (stock settings: shared_buffers=128MB, max_connections=100), no shared_preload_libraries.
Contract: diagnostics are read-only (pg_settings, pg_stat_*, EXPLAIN on SELECTs only). Every config change below is emitted ONLY as a ⚠️ HUMAN CONFIRMATION REQUIRED block — the postgres-dba agent never applies settings. Values marked ⚠️ are established heuristics, not guarantees: measure before and after every change, one parameter at a time.
Connection:
docker exec gc-platform-postgres psql -U gcplatform -d gcplatform -c "<query>"
1. Memory sizing vs the 1g mem_limit
Current settings (verify live):
SELECT name, setting, unit FROM pg_settings
WHERE name IN ('shared_buffers','effective_cache_size','work_mem','maintenance_work_mem',
'max_connections','huge_pages');
⚠️ Heuristic sizing for a dedicated 1g container:
| Parameter | Stock | Suggested | Rationale |
|---|---|---|---|
shared_buffers |
128MB | ≈ 256MB | Classic ⚠️ 25%-of-RAM heuristic; the container also needs room for per-backend memory, WAL buffers, and the OS page cache |
effective_cache_size |
4GB (!) | ≈ 512–768MB | Planner hint for "how much caching exists total" (shared_buffers + OS cache). Stock 4GB is a lie on a 1g container and biases the planner toward index scans it shouldn't trust |
work_mem |
4MB | keep 4–8MB | Allocated PER sort/hash node PER connection. Worst case ≈ max_connections × nodes-per-query × work_mem: 100 × 4 nodes × 8MB = 3.2GB ≫ 1g. Raising it globally is how containers OOM; raise per-session for known big sorts instead |
maintenance_work_mem |
64MB | 128–256MB | Used by VACUUM/CREATE INDEX; few concurrent users, safe to raise |
⚠️ HUMAN CONFIRMATION REQUIRED
# docker-compose.yml, postgres service (restart required):
command: ["postgres",
"-c", "shared_buffers=256MB",
"-c", "effective_cache_size=768MB",
"-c", "maintenance_work_mem=128MB"]
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.
- 27d ago First seen · 193 lines · 160 tokens per session scan A 6d43ec588ed0
postgres-performance-tuning is a skill published in the GitHub repository fmflurry/settings-opencode (171 stars, last pushed yesterday), licensed MIT. It adds 160 tokens to every session and 2,720 once invoked, about $0.0006 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 2026-09-20.
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