Better Agents is a command-line tool and set of standards for structuring, testing, evaluating, versioning, and observing AI-agent projects. It helps developers build agents with organized prompts, scenario tests, evaluation notebooks, and framework-specific guidance. Its catalogue rules guide coding assistants in applying this structure and these practices.
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/langwatch/better-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/rules/langwatch/better-agents/correction-response)<a href="https://agentmods.dev/rules/langwatch/better-agents/correction-response"><img src="https://agentmods.dev/badge/rules/langwatch/better-agents/correction-response/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/langwatch/better-agents/correction-response"><img src="https://agentmods.dev/badge/rules/langwatch/better-agents/correction-response.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 | $0.00319 | $0.00319 |
| Opus 5.5 | $0.00128 | $0.00128 |
| Sonnet 5.5 | $0.00064 | $0.00064 |
| Haiku 4.5 | $0.00032 | $0.00032 |
Grade A, and why
correction-response 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
Correction Response Rule
When corrected for doing something wrong, evaluate if it reveals a pattern that should become a rule. Only create/update rules for systemic issues, not one-off instructions.
Process:
- Acknowledge the correction and thank the user
- Ask for clarification if the correction seems like a one-off instruction vs. a principle
- Identify the root cause of the mistake
- Create or update a rule only for patterns that should be permanently avoided
- Apply the rule immediately to the current work if created
- Document the change clearly
Examples of Rule-Worthy Corrections:
- "no any in typescript" → Create typing rules (systemic principle)
- "rule too long" → Update rule formatting guidelines (process improvement)
- "use pnpm not npm" → Update tooling preferences (workflow consistency)
Examples of One-Off Instructions (Don't Make Rules):
- "skip the test" → Just skip this one test, don't change testing workflow
- "use red color here" → Specific UI choice, not a principle
- "name this variable foo" → Specific naming, not a pattern
When to Ask for Clarification:
- If the correction seems situational or temporary
- If it contradicts existing patterns/principles
- If you're unsure if it's a one-off or systemic issue
This ensures meaningful rule creation while respecting situational instructions.
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 · 33 lines · 319 tokens per session scan A f79efd8130cb
correction-response is a cursor rule published in the GitHub repository langwatch/better-agents (1,562 stars, last pushed 4mo ago), licensed MIT. It adds 319 tokens to every session, about $0.0013 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 2026-08-30.
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