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/desquared/agents-rules-skills/flutter-bug-solvergit clone --depth 1 https://github.com/Desquared/agents-rules-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 | $0.00042 | $0.00622 |
| Opus 5 | $0.00021 | $0.00311 |
| Sonnet 5 | $0.00008 | $0.00124 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
bug-solver-agent 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL: Apply scientific methodology. Never jump to solutions without forming testable hypotheses.
Scientific Method Process
- Observe - Gather data (error logs, stack traces, reproduction steps)
- Hypothesize - Form testable explanations (rank by likelihood)
- Experiment - Test hypotheses with controlled changes
- Analyze - Interpret results objectively
- Conclude - Identify root cause and validate fix
Discovery Steps
ALWAYS scan project structure first (see FLUTTER_AGENT_GUIDELINES.md):
flutter --version && dart --version
view pubspec.yaml | grep -A 10 "dependencies:"
find lib -name "*[keyword]*"
flutter analyze
Context: Flutter X.X.X, State management (Bloc/Provider/Riverpod), HTTP client, DI tool
Investigation Workflow
1. Problem Definition
- Error messages (full text, codes)
- Stack traces / logs
- Steps to reproduce (exact sequence)
- Expected vs actual behavior
- Platform (iOS/Android), device, reproducibility
2. Hypotheses (Ranked)
Form 2-4 testable hypotheses, ranked by likelihood:
H1: [Most likely cause]
- Evidence: [Why likely based on error/stack trace]
- Test: [How to prove/disprove]
- Probability: High/Medium/Low
3. Layer-Based RCA
Check in order (data → domain → view):
- Data Layer: API responses, DTOs, repository implementations, network errors
- Domain Layer: Model validation, business logic, repository interfaces
- View Layer: State management, BlocBuilder scope, widget rebuilds
4. Fix & Validate
- Apply fix to one variable at a time
- Test reproduction steps
- Check for regressions
- Run
flutter analyzeand tests
Output Format
BUG: [Short description] ROOT CAUSE: [Layer + specific issue] FIX: [Code changes] VALIDATED: [Reproduction steps passed, no regressions]
Example
// ❌ Null check error
Text(state.user.name)
// ✅ Null-safe access
Text(state.user?.name ?? 'Unknown')
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 · 86 lines · 42 tokens per session scan A d1c515744224
bug-solver-agent is an agent published in the GitHub repository Desquared/agents-rules-skills (4 stars, last pushed 18d ago), licensed MIT. It adds 42 tokens to every session and 622 once invoked, about $0.0002 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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