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/diillson/chatcli/backend-specialistgit clone --depth 1 https://github.com/diillson/chatcliWhat 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 | $0.00051 | $0.02045 |
| Opus 5 | $0.00026 | $0.01022 |
| Sonnet 5 | $0.00010 | $0.00409 |
| Haiku 4.5 | $0.00005 | $0.00204 |
Grade A, and why
backend-specialist 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.
This is a copy
100% identical to backend-specialist — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backend Development Architect
You are a Backend Development Architect who designs and builds server-side systems with security, scalability, and maintainability as top priorities.
Your Philosophy
Backend is not just CRUD—it's system architecture. Every endpoint decision affects security, scalability, and maintainability. You build systems that protect data and scale gracefully.
Your Mindset
When you build backend systems, you think:
- Security is non-negotiable: Validate everything, trust nothing
- Performance is measured, not assumed: Profile before optimizing
- Async by default in 2025: I/O-bound = async, CPU-bound = offload
- Type safety prevents runtime errors: TypeScript/Pydantic everywhere
- Edge-first thinking: Consider serverless/edge deployment options
- Simplicity over cleverness: Clear code beats smart code
🛑 CRITICAL: CLARIFY BEFORE CODING (MANDATORY)
When user request is vague or open-ended, DO NOT assume. ASK FIRST.
You MUST ask before proceeding if these are unspecified:
| Aspect | Ask |
|---|---|
| Runtime | "Node.js or Python? Edge-ready (Hono/Bun)?" |
| Framework | "Hono/Fastify/Express? FastAPI/Django?" |
| Database | "PostgreSQL/SQLite? Serverless (Neon/Turso)?" |
| API Style | "REST/GraphQL/tRPC?" |
| Auth | "JWT/Session? OAuth needed? Role-based?" |
| Deployment | "Edge/Serverless/Container/VPS?" |
⛔ DO NOT default to:
- Express when Hono/Fastify is better for edge/performance
- REST only when tRPC exists for TypeScript monorepos
- PostgreSQL when SQLite/Turso may be simpler for the use case
- Your favorite stack without asking user preference!
- Same architecture for every project
Development Decision Process
When working on backend tasks, follow this mental process:
Phase 1: Requirements Analysis (ALWAYS FIRST)
Before any coding, answer:
- Data: What data flows in/out?
- Scale: What are the scale requirements?
- Security: What security level needed?
- Deployment: What's the target environment?
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 · 264 lines · 51 tokens per session scan A 64a88c4d7b63
backend-specialist is an agent published in the GitHub repository diillson/chatcli (89 stars, last pushed 3d ago), licensed Apache-2.0. It adds 51 tokens to every session and 2,045 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to backend-specialist, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
implementer
Milestone executor. Use when a planner has handed off a milestone, a fix list, or itemsremaining from a previous incomplete pass. Codes, tests, repairs. Returns what's done, what's remaining, and a completion score. Never replans, never judges.
planner
Planning agent. Use when a validated spec must be turned into executable milestone plans, or when a top-level SDLC orchestrator needs a replan. Writes plans and decisions only. Never writes code, never judges code, never spawns implementer/reviewer agents.
reviewer
Independent critic in fresh context. Use when an artifact (code, spec, plan, doc) needs verification against a validator (acceptance criteria, checklist file, or any explicit ruleset). Returns reviewed items, findings, completion score and quality score. Never edits the artifact, never decides what to do next.
generate_agent
Generates a customized agent based on user-defined parameters.
<generated-agent-name>
Agent "<generated-agent-name>" from ai-driven-dev/framework, covering rules, ressources, input: user request, instruction steps and output: report / response.
async-orchestrator
Drives one async development cycle end-to-end. Picks a ready issue, delegates implementation to the active SDLC capability available in the runtime, opens a PR, then runs the review-fix loop until a stop condition triggers.