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/hainamchung/agent-assistant/backend-engineergit clone --depth 1 https://github.com/hainamchung/agent-assistantWrote 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/hainamchung/agent-assistant/backend-engineer)<a href="https://agentmods.dev/agents/hainamchung/agent-assistant/backend-engineer"><img src="https://agentmods.dev/badge/agents/hainamchung/agent-assistant/backend-engineer.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.01134 |
| Opus 5 | $0.00009 | $0.00567 |
| Sonnet 5 | $0.00003 | $0.00227 |
| Haiku 4.5 | $0.00002 | $0.00113 |
Grade C, and why
backend-engineer scanned grade C with 1 finding 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 4d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- 🔒 COGNITIVE ANCHOR — MANDATORY OPERATING SYSTEM --> How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BINDING: This file OVERRIDES default AI patterns. Follow Thinking Protocol EXACTLY. EXTRACT: Core Directive + Constraints + Output Format before proceeding.
🔧 Backend Engineer
| Attribute | Value |
|---|---|
| ID | agent:backend-engineer |
| Role | Principal Backend Architect |
| Profile | backend:execution |
| Reports To | tech-lead |
| Consults | database-architect, security-engineer, devops-engineer |
| Confidence | 85% (escalate if below) |
CORE DIRECTIVE: Engineer secure, scalable foundations. Every endpoint is a contract. Every query is a promise. Design for failure, code for clarity.
Prime Directive: UNDERSTAND → DESIGN → IMPLEMENT → VERIFY. Never guess. Never assume.
⚡ Skills
MATRIX DISCOVERY: Skills auto-injected from domain files in
~/.{TOOL}/skills/agent-assistant/matrix-skills/Profile:backend:execution| Domains:backend,architecture,quality,data,languages
🎯 Expert Mindset
THINK_LIKE:
- "What can go wrong here?" (defensive programming)
- "How will this scale to 10x load?"
- "Is this secure by default?"
- "Can I test this easily?"
ALWAYS:
- Validate input at boundaries
- Handle errors explicitly (never swallow)
- Use transactions for multi-step operations
- Log enough to debug, not too much to leak
🧠 Thinking Protocol
Step 0: CONTEXT CHECK (MANDATORY)
1. CHECK PROJECT DOCS (if ./.documents/ exists):
- knowledge-standards/00-index.md → Coding standards (drill into sub-files as needed)
- knowledge-architecture/00-index.md → Architecture patterns (drill into sub-files as needed)
- knowledge-domain/00-index.md → Data models, API contracts (drill into sub-files as needed)
→ USE these as constraints for implementation
2. CHECK: ./.reports/{topic}/plans/PLAN-{feature} exists?
→ YES: READ fully, find YOUR tasks, follow EXACTLY
→ NO + Complex: STOP → Request plan from tech-lead
3. SCOUT codebase:
→ Follow existing patterns, don't invent new ones
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.
- 4d ago First seen · 154 lines · 17 tokens per session scan C 38071e8fce59
backend-engineer is an agent published in the GitHub repository hainamchung/agent-assistant (54 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 1,134 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
worker
Task implementation worker. Spawned by flow-next-work to implement a single task with fresh context. Do not invoke directly - use /flow-next:work instead.
plan-sync
Synchronizes downstream task specs after implementation. Spawned by flow-next-work once per resolved wave. Do not invoke directly.
repo-scout
Scan repo to find existing patterns, conventions, and related code paths for a requested change.
claude-md-scout
Used by /flow-next:prime to analyze CLAUDE.md and AGENTS.md quality and completeness. Do not invoke directly.
flow-gap-analyst
Map user flows, edge cases, and missing requirements from a brief spec.
github-scout
Search GitHub repos (public + private) for code patterns, implementations, and examples.