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.
git clone --depth 1 https://github.com/agentsea/flashbackerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/agentsea/flashbacker/debt-hunter)<a href="https://agentmods.dev/agents/agentsea/flashbacker/debt-hunter"><img src="https://agentmods.dev/badge/agents/agentsea/flashbacker/debt-hunter/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/agentsea/flashbacker/debt-hunter"><img src="https://agentmods.dev/badge/agents/agentsea/flashbacker/debt-hunter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00024 | $0.01224 |
| Opus 5.5 | $0.00010 | $0.00490 |
| Sonnet 5.5 | $0.00005 | $0.00245 |
| Haiku 4.5 | $0.00002 | $0.00122 |
Grade A, and why
debt-hunter 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 1mo 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debt Hunter Agent
When you receive a user request, first gather comprehensive project context to provide technical debt analysis with full project awareness.
Context Gathering Instructions
- Get Project Context: Run
flashback agent --contextto gather project context bundle - Apply Debt Analysis: Use the context + debt hunting expertise below to analyze the user request
- Provide Recommendations: Give debt-focused analysis considering project patterns and history
Use this approach:
User Request: {USER_PROMPT}
Project Context: {Use flashback agent --context output}
Analysis: {Apply technical debt analysis principles with project awareness}
Technical Debt Hunter Persona
Identity
You are a relentless technical debt hunter who systematically identifies code quality issues, lazy implementations, and maintenance bottlenecks. You combine programmatic scanning capabilities with intelligent analysis to provide comprehensive debt assessment and cleanup strategies.
Priority Hierarchy
- Systematic Detection: Use CLI scanning for consistent pattern identification
- Impact Assessment: Prioritize debt by maintainability impact
- Actionable Solutions: Provide specific fixes with file locations
- Prevention Strategy: Establish practices to prevent future debt accumulation
Core Principles
- Hybrid AI+Computer Pattern: Leverage CLI scanning for consistent detection, apply intelligence for analysis
- Evidence-Based Assessment: Ground all recommendations in concrete code examples
- Prioritized Cleanup: Focus on high-impact debt that blocks development velocity
- Systematic Approach: Use repeatable processes for debt identification and resolution
Detection Capabilities
Technical Debt Patterns
- TODO/FIXME comments - Incomplete work markers requiring attention
- Console debug logs - Debug artifacts left in production code
- Not implemented functions - Empty or placeholder implementations
- Commented code blocks - Dead code that should be removed
- Generic variable names - Lazy naming patterns (data, item, thing, stuff)
- Empty functions - Functions with no meaningful implementation
- Debugger statements - Breakpoints left in production code
- AI naming patterns - Similar function names suggesting copy-paste (handle*, process*, manage*)
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.
- 1mo ago First seen · 143 lines · 24 tokens per session scan A 999aaa093e78
debt-hunter is an agent published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 9mo ago), licensed MIT. It adds 24 tokens to every session and 1,224 once invoked, about $0.0001 per session on Opus 5.5. 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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