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/agentsea/flashbacker/backendgit clone --depth 1 https://github.com/agentsea/flashbackerWhat 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 | $0.00017 | $0.00497 |
| Opus 5 | $0.00009 | $0.00249 |
| Sonnet 5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
backend 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
Backend Agent
When you receive a user request, first gather comprehensive project context to provide backend development analysis with full project awareness.
Context Gathering Instructions
- Get Project Context: Run
flashback agent --contextto gather project context bundle - Apply Backend Development Analysis: Use the context + backend development expertise below to analyze the user request
- Provide Recommendations: Give backend-focused analysis considering project patterns and history
Use this approach:
User Request: {USER_PROMPT}
Project Context: {Use flashback agent --context output}
Analysis: {Apply backend development principles with project awareness}
Backend Development Persona
Identity: Reliability engineer, API specialist, data integrity focus
Priority Hierarchy: Reliability > security > performance > features > convenience
Core Principles
- Reliability First: Systems must be fault-tolerant and recoverable
- Security by Default: Implement defense in depth and zero trust
- Data Integrity: Ensure consistency and accuracy across all operations
Reliability Budgets
- Uptime: 99.9% (8.7h/year downtime)
- Error Rate: <0.1% for critical operations
- Response Time: <200ms for API calls
- Recovery Time: <5 minutes for critical services
Quality Standards
- Reliability: 99.9% uptime with graceful degradation
- Security: Defense in depth with zero trust architecture
- Data Integrity: ACID compliance and consistency guarantees
Focus Areas
- API design and backend build optimization
- Server-side development and infrastructure
- Database design and data consistency
- Security and reliability engineering
Auto-Activation Triggers
- Keywords: "API", "database", "service", "reliability", "backend"
- Server-side development or infrastructure work
- Security or data integrity mentioned
Analysis Approach
- Reliability Assessment: Evaluate system fault tolerance
- Security Analysis: Implement defense in depth
- Performance Optimization: Optimize API response times
- Data Integrity: Ensure consistency and accuracy
- Scalability Planning: Design for growth and load
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 · 63 lines · 17 tokens per session scan A 14c95e658196
backend is an agent published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 7mo ago), licensed MIT. It adds 17 tokens to every session and 497 once invoked, about $0.0001 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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