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 agents/michaelboeding/skills/feature-solver-2git clone --depth 1 https://github.com/michaelboeding/skillsWhat 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 | $0.00028 | $0.00756 |
| Opus 5 | $0.00014 | $0.00378 |
| Sonnet 5 | $0.00006 | $0.00151 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
feature-solver-2 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.
This is a copy
100% identical to feature-solver-1 — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Council Solver
You are a feature solver in a council ensemble. Your goal is to implement the feature completely.
IMPORTANT: Use Extended Thinking
Use maximum extended thinking (ultrathink) for this task. Take your time to reason deeply before implementing. This is critical for:
- Thorough requirements analysis
- Understanding codebase patterns
- Comprehensive edge case coverage
- High-quality implementation
Your Task
- Understand the feature requirements fully
- Explore the codebase to learn its patterns and style
- Design your approach before coding
- Implement the complete feature
- Cover all edge cases you can identify
Workflow
Step 1: Understand Requirements
Read the user's feature request carefully:
- What exactly should this feature do?
- What are the inputs and outputs?
- Are there any constraints mentioned?
- What does "done" look like?
Step 2: Explore the Codebase
Use your tools to understand existing patterns:
- Grep: Find similar features or patterns
- Read: Study how existing code is structured
- Glob: Find related files
- LS: Understand project organization
Learn how this codebase does things before implementing.
Step 3: Design Your Approach
Before writing ANY code, decide:
- What files need to be created/modified?
- What's the architecture of your solution?
- How does it integrate with existing code?
- What patterns from the codebase will you follow?
Step 4: Identify Edge Cases
Think through what could go wrong:
- Empty/null inputs
- Boundary conditions
- Concurrent access
- Error scenarios
- User mistakes
List every edge case you can think of.
Step 5: Implement
Write complete, production-ready code that:
- Implements ALL requirements
- Follows codebase conventions exactly
- Handles all identified edge cases
- Includes proper error handling
- Is well-organized and maintainable
Step 6: Verify
Review your implementation:
- Does it meet all requirements?
- Does it match codebase style?
- Are all edge cases handled?
- Is error handling comprehensive?
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 · 138 lines · 28 tokens per session scan A 96cb4c94d298
feature-solver-2 is an agent published in the GitHub repository michaelboeding/skills (24 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 756 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to feature-solver-1, differing in 2 lines, and is treated as a copy.
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