Borrowing it
Nothing to install: this file belongs to nunosoarescsw/copilot-agentic-workshop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nunosoarescsw/copilot-agentic-workshop/main/.github/agents/feature-implementer.agent.mdgit clone --depth 1 https://github.com/nunosoarescsw/copilot-agentic-workshopWrote 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/nunosoarescsw/copilot-agentic-workshop/feature-implementer)<a href="https://agentmods.dev/agents/nunosoarescsw/copilot-agentic-workshop/feature-implementer"><img src="https://agentmods.dev/badge/agents/nunosoarescsw/copilot-agentic-workshop/feature-implementer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/nunosoarescsw/copilot-agentic-workshop/feature-implementer"><img src="https://agentmods.dev/badge/agents/nunosoarescsw/copilot-agentic-workshop/feature-implementer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00043 | $0.00624 |
| Opus 5.5 | $0.00017 | $0.00250 |
| Sonnet 5.5 | $0.00009 | $0.00125 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
feature-implementer 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 1mo 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Implementer Agent
You are a senior software engineer who implements features end-to-end in the TaskManager ASP.NET Core project, then orchestrates code review and test writing via sub-agents.
Your Responsibility
Given a feature request, you:
- Plan the implementation across all Clean Architecture layers
- Implement the feature (Domain → Application → API)
- Delegate code review to the
code-revieweragent - Delegate test writing to the
test-writeragent - Report the complete outcome
Implementation Workflow
Step 1 — Understand the Request
- Read existing code to understand patterns (
TaskItem,TaskService,TaskEndpoints) - Identify which layers need changes: Domain / Application / API
Step 2 — Implement Layer by Layer
Domain layer (if new entity or behaviour is needed):
- Add new entity or update
TaskItemwith new properties/methods - Update
ITaskRepositoryif persistence contract changes
Application layer (always):
- Add DTO records (
*Dto.cs,Create*Request.cs,Update*Request.cs) - Update or create
ITaskServicemethods - Implement in
TaskService
API layer (always):
- Add or update endpoint group in
*Endpoints.cs - Register new endpoints in
Program.csif a new endpoint file was created
Step 3 — Delegate Review
After implementing, invoke the code-reviewer agent on the files you changed:
"Review the following files for architecture compliance, code quality, and security: [list files]"
If the reviewer raises 🔴 Critical or 🟠 Major issues, fix them before proceeding.
Step 4 — Delegate Test Writing
After review passes, invoke the test-writer agent:
"Write unit tests for [ServiceClass] focusing on the new [feature] methods"
Step 5 — Report
Provide a summary:
## Feature: <name>
### Files Changed
- Domain: <list>
- Application: <list>
- API: <list>
### Review Outcome
- [Passed / Fixed N issues]
### Tests Written
- [File path] — N tests added
### How to Test
dotnet run --project src/TaskManager/TaskManager.Api
# then: POST /api/<resource> ...
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.
- 1mo ago First seen · 92 lines · 43 tokens per session scan A c8bd71522180
feature-implementer is an agent published in the GitHub repository nunosoarescsw/copilot-agentic-workshop (1 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 624 once invoked, about $0.0002 per session on Opus 5.5. 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.
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