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/systemowiec/ai-agents-workspace-starter/backend-engineergit clone --depth 1 https://github.com/systemowiec/ai-agents-workspace-starterWrote 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/systemowiec/ai-agents-workspace-starter/backend-engineer)<a href="https://agentmods.dev/agents/systemowiec/ai-agents-workspace-starter/backend-engineer"><img src="https://agentmods.dev/badge/agents/systemowiec/ai-agents-workspace-starter/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 5.1 | $0.00044 | $0.00314 |
| Opus 5 | $0.00022 | $0.00157 |
| Sonnet 5 | $0.00009 | $0.00063 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
backend-engineer 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 5d 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
Read and apply strictly:
.agents/roles/backend-engineer.md- full role definition.agents/skills/add-endpoint/SKILL.md- endpoint patterns.agents/skills/database-migration/SKILL.md- migration patterns.agents/skills/write-python-tests/SKILL.md- test patterns.agents/rules/global.md- Cardinal RulesAGENTS.md(root) - global rules.agents/learnings/gotchas.md- known gotchas
Golden rule
Business logic EXCLUSIVELY in services. NEVER in routers/views, models, schemas/serializers.
Mandatory workflow
BEFORE implementation read workflows/spec-development.md.
AFTER implementation run workflows/post-impl-verify.md.
When finished
- Run:
make test+make lint - Update
.agents/context/api-map.mdif you changed endpoints - Save report in
docs/specs/{layer}/{PREFIX}-NNN/impl-backend-engineer.md - Inform: "Implementation complete. Report ready for review."
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.
- 5d ago First seen · 36 lines · 44 tokens per session scan A 7b8e63fc3f47
backend-engineer is an agent published in the GitHub repository systemowiec/ai-agents-workspace-starter (2 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 314 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
Geoprocessing Specialist
ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.
python-pro
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use PROACTIVELY for Python refactoring, optimization, or complex Python features.
fsl-vacuity-reviewer
Use PROACTIVELY after adding or changing a .fsl spec under specs/ or examples/. Uses the working-tree native Rust CLI to detect hollowing, weak mutation kill-rate, vacuous properties, and weakened invariants. Read-only on specs; may run verifier commands.
python-pytest-architect
Creates, reviews, and modernizes Python 3.11+ test suites using pytest. Expert in pytest-mock (not unittest.mock), hypothesis property-based testing, pytest-asyncio, and pytest-bdd. Enforces 80% coverage minimum, AAA pattern, and mutation testing for critical code.
python-spec
Python 3.12+ 전문가. async, uv, ruff, pydantic, 모던 Python 생태계. "Python", "파이썬", "async", "uv", "ruff" 요청에 실행.
python-worker-reviewer
Reviews standalone Python background worker services (Pub/Sub, Cloud Scheduler, GCS-triggered). Checks error surfacing, external client injection, DB access patterns, structlog usage, and test coverage. Use after any changes to worker services that are not FastAPI REST APIs or ADK agents.