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 skills/umputun/cc-thingz/wrongnpx skills add umputun/cc-thingz --skill wronggit clone --depth 1 https://github.com/umputun/cc-thingzWhat 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 | $0.00058 | $0.00388 |
| Opus 5 | $0.00029 | $0.00194 |
| Sonnet 5 | $0.00012 | $0.00078 |
| Haiku 4.5 | $0.00006 | $0.00039 |
Grade A, and why
wrong 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
Wrong — Reset and Re-evaluate
The current approach isn't working as expected. Step back and re-examine the problem from the beginning.
Workflow
Step 1: Re-analyze the Core Problem
State the problem in clear, simple terms. What exactly are we trying to solve?
Step 2: Identify Missing Context
Determine what additional information is needed about:
- The existing codebase and its patterns
- Performance requirements or constraints
- Integration points with other systems
- Expected usage patterns or scale
- Any domain-specific requirements not yet mentioned
Step 3: Propose Fresh Approaches
Suggest 2-3 alternative solutions that:
- Follow project best practices and idioms
- Match the existing code's style and architecture patterns
- Are maintainable and testable
- Solve the exact problem without over-engineering
- Don't use shortcuts or hacks
Step 4: Explain Trade-offs
For each proposed approach, briefly explain:
- Why this approach fits the problem
- What the main benefits and drawbacks are
- How it integrates with the existing codebase
Step 5: Recommend the Best Path Forward
Which approach is most appropriate and why?
Requirements
- Solution must be production-ready, not a proof of concept
- Code should be idiomatic and follow established patterns
- Include comprehensive tests with edge cases
- Provide complete, runnable code with no placeholders
- Ensure the solution is maintainable
Ask clarifying questions before proceeding.
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 · 55 lines · 58 tokens per session scan A f3688ed21d49
wrong is a skill published in the GitHub repository umputun/cc-thingz (460 stars, last pushed 8d ago), licensed MIT. It adds 58 tokens to every session and 388 once invoked, about $0.0003 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 2026-08-30.
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