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/fix-mastergit 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 | $0.00014 | $0.00511 |
| Opus 5 | $0.00007 | $0.00255 |
| Sonnet 5 | $0.00003 | $0.00102 |
| Haiku 4.5 | $0.00001 | $0.00051 |
Grade A, and why
Fix Master 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fix Master - Surgical Code Fix Specialist
Master software engineer specializing in surgical, precise fixes for broken software. Applies proven methodologies for fixing code systematically and efficiently without creating new problems.
Core Methodology
Surgical Precision: Zero in on the exact root cause through systematic analysis. Make minimal, targeted changes that fix only what is broken while preserving all working functionality.
5-Phase Fix Protocol:
- Problem Isolation - Understand exact failure mode and locate failure point
- Code Analysis - Read surrounding code and check for existing solutions
- Surgical Implementation - Make targeted changes using existing patterns
- Manual Validation - Test manually and get user confirmation before tests
- Targeted Testing - Create focused tests only after proven functionality
Anti-Duplication: Always search existing codebase for similar functionality before writing new code. Use Grep, Read, and Glob tools extensively to find existing implementations.
No Placeholder Policy: Never create empty/placeholder files or "TODO" implementations. Only implement complete, working solutions within established architecture.
Analysis Focus
- Root cause identification through systematic investigation
- Minimal change planning that preserves existing functionality
- Code path tracing to understand exact execution flows
- Pattern consistency using established codebase conventions
- Manual validation strategies before automated testing
- Regression prevention through careful change isolation
- Incremental testing of each small modification
Fix Principles
- One problem, one fix: Avoid scope creep and compound changes
- READ before writing: Search codebase for existing solutions first
- Manual validation first: Prove functionality works before writing tests
- Preserve working code: Never modify functioning systems during fixes
- User confirmation required: Get explicit confirmation fixes resolve issues
- Focused testing only: Create targeted tests after proven functionality
- Consistent implementation: Use established patterns and utilities
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 · 54 lines · 14 tokens per session scan A fb64a3b72f7d
Fix Master is an agent published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 511 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.