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/sarkarsaurabh27/agent-loop-learningWrote 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/rules/sarkarsaurabh27/agent-loop-learning/best-practices)<a href="https://agentmods.dev/rules/sarkarsaurabh27/agent-loop-learning/best-practices"><img src="https://agentmods.dev/badge/rules/sarkarsaurabh27/agent-loop-learning/best-practices/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/rules/sarkarsaurabh27/agent-loop-learning/best-practices"><img src="https://agentmods.dev/badge/rules/sarkarsaurabh27/agent-loop-learning/best-practices.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 | $0.00043 | $0.00373 |
| Opus 5.5 | $0.00017 | $0.00149 |
| Sonnet 5.5 | $0.00009 | $0.00075 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
best-practices 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.
What it actually says
Load Best Practice Reference
When the user asks for best practices on a topic:
- Match the topic keyword:
| Keyword | File |
|---|---|
| orchestration / multi-agent | best-practices/01-multi-agent-orchestration.md |
| worker | best-practices/02-worker-prompting.md |
| prompting | best-practices/02-worker-prompting.md + 07-prompt-engineering.md |
| memory / context / rag | best-practices/03-context-and-memory.md |
| tools | best-practices/04-tool-design.md |
| verification / testing | best-practices/05-verification-and-testing.md |
| security / permissions | best-practices/06-security-and-permissions.md |
| performance / startup | best-practices/08-performance-and-startup.md |
| benchmarks | best-practices/09-benchmarks-reference.md |
| all | all docs |
-
Read the matched file(s).
-
Present with this structure:
- Key benchmarks — the "Benchmarks at a Glance" table from the doc
- Core principles — 3–5 bullet summary
- Full document — complete content
- How to apply — 2–3 self-check questions for the user's own agent
-
If no keyword, show
best-practices/README.mdindex and ask which topic.
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 · 35 lines · 43 tokens per session scan A e23076c21de1
best-practices is a cursor rule published in the GitHub repository sarkarsaurabh27/agent-loop-learning (3 stars, last pushed 5mo ago), licensed MIT. It adds 43 tokens to every session and 373 once invoked, about $0.0002 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 2026-08-31.
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