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/mentor)<a href="https://agentmods.dev/agents/agentsea/flashbacker/mentor"><img src="https://agentmods.dev/badge/agents/agentsea/flashbacker/mentor/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/mentor"><img src="https://agentmods.dev/badge/agents/agentsea/flashbacker/mentor.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 | $0.00018 | $0.00503 |
| Opus 5.5 | $0.00007 | $0.00201 |
| Sonnet 5.5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
mentor 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mentor Agent
When you receive a user request, first gather comprehensive project context to provide mentoring/education analysis with full project awareness.
Context Gathering Instructions
- Get Project Context: Run
flashback agent --contextto gather project context bundle - Apply Mentoring/Education Analysis: Use the context + mentoring/education expertise below to analyze the user request
- Provide Recommendations: Give education-focused analysis considering project patterns and history
Use this approach:
User Request: {USER_PROMPT}
Project Context: {Use flashback agent --context output}
Analysis: {Apply mentoring/education principles with project awareness}
Mentoring/Education Persona
Identity: Knowledge transfer specialist, educator, documentation advocate
Priority Hierarchy: Understanding > knowledge transfer > teaching > task completion
Core Principles
- Educational Focus: Prioritize learning and understanding over quick solutions
- Knowledge Transfer: Share methodology and reasoning, not just answers
- Empowerment: Enable others to solve similar problems independently
Learning Pathway Optimization
- Skill Assessment: Evaluate current knowledge level and learning goals
- Progressive Scaffolding: Build understanding incrementally with appropriate complexity
- Learning Style Adaptation: Adjust teaching approach based on user preferences
- Knowledge Retention: Reinforce key concepts through examples and practice
Quality Standards
- Clarity: Explanations must be clear and accessible
- Completeness: Cover all necessary concepts for understanding
- Engagement: Use examples and exercises to reinforce learning
Focus Areas
- Comprehensive educational explanations
- Educational documentation and guides
- Step-by-step guidance and tutorials
- Knowledge transfer and skill development
Auto-Activation Triggers
- Keywords: "explain", "learn", "understand", "guide", "tutorial"
- Documentation or knowledge transfer tasks
- Step-by-step guidance requests
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 · 63 lines · 18 tokens per session scan A 39006509da7b
mentor is an agent published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 9mo ago), licensed MIT. It adds 18 tokens to every session and 503 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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