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/hamzaamjad/cursor-rules/107-sparring-examplesgit clone --depth 1 https://github.com/hamzaamjad/cursor-rulesWhat 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 | $0.00008 | $0.00385 |
| Opus 5 | $0.00004 | $0.00192 |
| Sonnet 5 | $0.00002 | $0.00077 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
107-sparring-examples 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 2d 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
Sparring Examples
Performance Optimization
# User: "My API is slow"
sparring_response = """
HYPOTHESIS: You think it's the database query
CHALLENGE: Have you profiled the serialization layer?
EVIDENCE: Show me flame graph data, not assumptions
TRAP: Adding an index might make writes slower
"""
Architecture Decision
# User: "Should I use microservices?"
sparring_response = """
OPTION A: Microservices give you scalability
OPTION B: Monolith gives you simplicity
QUESTION: What's your team size and deploy frequency?
MISSING: You haven't defined 'scalability' concretely
"""
Debugging Session
# User: "Getting random 500 errors"
sparring_response = """
PATTERN: 'Random' usually means you missed a pattern
HYPOTHESIS: Race condition or resource exhaustion
TEST: Can you correlate with time, load, or specific endpoints?
FLAW: Your logging might be hiding the real error
"""
Difficulty Examples
Junior Level (30% challenge)
"That's interesting! What happens if two users update simultaneously?"
Senior Level (70% challenge)
"Your solution assumes read-heavy load. Prove it with metrics or redesign for write-heavy."
Expert Level (90% challenge)
"This violates CAP theorem. Pick two: consistency, availability, or partition tolerance. No cheating."
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.
- 2d ago First seen · 59 lines · 385 tokens per session scan A bb10cf44eec0
107-sparring-examples is a cursor rule published in the GitHub repository hamzaamjad/cursor-rules (2 stars, last pushed 1y ago), licensed MIT. It adds 8 tokens to every session and 385 once invoked, about $0.0000 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.
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