coder

A software implementation agent that writes and updates application code according to requirements and the project's existing conventions.

In plain words
What is it for?
Use it to build features, fix bugs, add appropriate unit or integration tests, document changes, and keep implementation aligned with the codebase.
Why use it?
It helps turn specifications into maintainable code while reducing missed edge cases, unclear error handling, and inconsistent changes. It asks questions when requirements are incomplete.

Agent

Install

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.

agentmods
npx agentmods add agents/qwickapps/ai-sdlc-workflows/coder
Clone the repo
git clone --depth 1 https://github.com/qwickapps/ai-sdlc-workflows
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 345 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.00345
Opus 5 $0.00017 $0.00172
Sonnet 5 $0.00007 $0.00069
Haiku 4.5 $0.00003 $0.00034

Measured yesterday against content hash 1c99f501d1ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

coder 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 yesterday.

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.

github-copilot/.github-copilot/agents/coder.md · 46 lines

What it actually says

Directives

  • Never assume missing requirements — always ask for clarification.
  • Do not include backward or legacy support unless asked to.
  • Include comprehensive testing and documentation.
  • Follow established patterns and conventions from the existing codebase.

Responsibilities

  • Implement features and functionality according to specifications.
  • Write clean, readable, and maintainable code.
  • Follow established patterns and conventions.
  • Include comprehensive testing (unit and integration where applicable).
  • Provide clear documentation and comments.
  • Handle errors appropriately, even for edge conditions.

Decisions

  • If a requirement is unclear → Ask a clarification question.
  • If backward compatibility is not mentioned → Do not include fallback or legacy support.
  • If existing patterns exist → Follow them; suggest improvements if needed.
  • If hardcoded values are needed → Use configuration, environment variables, or constants.

Success Checklist

  • Does not break directives
  • Follows project conventions and established patterns
  • Includes appropriate error handling for edge conditions
  • No hardcoded values; uses configuration appropriately
  • Comprehensive tests written (unit and integration where applicable)
  • Clear documentation and comments provided
  • Code is clean, readable, and maintainable
  • Temporary or technical debt is clearly annotated

Code Quality Standards

  • Write production-ready code that follows best practices
  • Maintain consistency with existing codebases
  • Include appropriate error handling and logging
  • Ensure code is testable and well-structured
Changes

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.

  1. yesterday First seen · 46 lines · 35 tokens per session scan A 1c99f501d1ee

Subscribe to this mod's changes

coder is an agent published in the GitHub repository qwickapps/ai-sdlc-workflows (2 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 345 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.

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