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 agentmods add rules/bia-technologies/yaxunit/reflection-basicgit clone --depth 1 https://github.com/bia-technologies/yaxunitWhat 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 | $0.01232 | $0.01232 |
| Opus 5 | $0.00616 | $0.00616 |
| Sonnet 5 | $0.00246 | $0.00246 |
| Haiku 4.5 | $0.00123 | $0.00123 |
Grade A, and why
reflection-basic 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 today.
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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BASIC REFLECTION FOR LEVEL 2 TASKS
TL;DR: This document outlines a basic reflection approach for Level 2 (Simple Enhancement) tasks, ensuring that key insights and lessons are captured without unnecessary overhead.
🔍 REFLECTION OVERVIEW
Reflection is essential for improving future work, even for simpler Level 2 enhancements. This basic reflection approach focuses on key outcomes, challenges, and lessons learned while maintaining efficiency.
📋 REFLECTION PRINCIPLES
- Honesty: Accurately represent successes and challenges
- Specificity: Include concrete examples and observations
- Insight: Go beyond surface observations to derive useful insights
- Improvement: Focus on actionable takeaways for future work
- Efficiency: Keep reflection concise and focused on key learnings
📋 BASIC REFLECTION STRUCTURE
# Level 2 Enhancement Reflection: [Feature Name]
## Enhancement Summary
[Brief one-paragraph summary of the enhancement]
## What Went Well
- [Specific success point 1]
- [Specific success point 2]
- [Specific success point 3]
## Challenges Encountered
- [Specific challenge 1]
- [Specific challenge 2]
- [Specific challenge 3]
## Solutions Applied
- [Solution to challenge 1]
- [Solution to challenge 2]
- [Solution to challenge 3]
## Key Technical Insights
- [Technical insight 1]
- [Technical insight 2]
- [Technical insight 3]
## Process Insights
- [Process insight 1]
- [Process insight 2]
- [Process insight 3]
## Action Items for Future Work
- [Specific action item 1]
- [Specific action item 2]
- [Specific action item 3]
## Time Estimation Accuracy
- Estimated time: [X hours/days]
- Actual time: [Y hours/days]
- Variance: [Z%]
- Reason for variance: [Brief explanation]
📋 REFLECTION QUALITY
High-quality reflections for Level 2 tasks should:
- Provide specific examples rather than vague statements
- Identify concrete takeaways not general observations
- Connect challenges to solutions with clear reasoning
- Analyze estimation accuracy to improve future planning
- Generate actionable improvements for future work
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.
- today First seen · 178 lines · 1,232 tokens per session scan A d65b57dfe0d7
reflection-basic is a cursor rule published in the GitHub repository bia-technologies/yaxunit (322 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 1,232 tokens to every session, about $0.0062 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 2026-09-01.
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model-selection
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zpa-dependency-chain
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