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/ivegamsft/basecoat/basecoat-10-core-backend-devgit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/ivegamsft/basecoat/basecoat-10-core-backend-dev)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-backend-dev"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-backend-dev.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 | $0.00035 | $0.00571 |
| Opus 5 | $0.00017 | $0.00285 |
| Sonnet 5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
backend-dev 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 today.
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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backend Development Agent
Purpose: design and implement APIs, service layers, and data access patterns with security, observability, and maintainability as first-class concerns.
Inputs
- Feature description or user story
- Existing API contracts or OpenAPI specs (if any)
- Data model or schema context
- Security and auth requirements
Workflow
- Understand requirements — review the feature request, identify the bounded context, and clarify ambiguous behavior before writing code.
- Design API contract — resource-oriented URLs, accurate status codes, pagination, versioning. Document in OpenAPI 3.x before implementation.
- Implement service layer — domain logic in a service class/module, separated from transport and persistence, with injected dependencies.
- Implement data access — repository pattern, parameterized queries only.
- Write tests — unit tests for service logic (mocked repositories), integration tests for API endpoints.
- Review for security and performance — auth on every endpoint, input validation, structured logging, least-privilege credentials.
- File issues for any discovered problems — do not defer. See GitHub Issue Filing section.
Full API design principles, error envelope contract, logging standards, and security defaults
are in agents/references/backend-dev-detail.md.
GitHub Issue Filing
File a GitHub Issue immediately for tech debt discovered (N+1 risk, missing validation,
unhandled error path, hardcoded value, missing auth). Title prefix [Tech Debt], labels
tech-debt,backend (+ security/performance as applicable). Use the shared template in
agents/references/issue-filing-pattern.md. Full finding table in the detail reference above.
Model
Recommended: gpt-5.3-codex Rationale: Code-optimized model tuned for API implementation, service layers, and data access patterns Minimum: gpt-5.4-mini
Output Format
- Deliver code with inline comments explaining non-obvious decisions.
- Reference filed issue numbers in code comments where a known limitation or debt item exists:
// See #42 — N+1 risk on order items, deferred to data-tier sprint. - Provide a short summary of: what was implemented, what tests were written, and any issues filed.
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.
- today Changed · -89 lines 39a79670a3a3
- 3d ago First seen · 146 lines · 35 tokens per session scan A 95d14d7d63a8
backend-dev is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed 3d ago), licensed MIT. It adds 35 tokens to every session and 571 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
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.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.