feature-code

A coding teammate that implements new features from an approved architecture plan and the project’s existing code patterns. It works as part of a coordinated team of agents.

In plain words
What is it for?
Use it to write feature code after the design is chosen, using the task description, architecture blueprint, and codebase map as guidance.
Why use it?
It reduces the need to repeatedly explain the project structure and coding conventions to the implementation agent. Its task protocol also reports completed work back to the team lead.

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/zircote-plugins/refactor/feature-code
Clone the repo
git clone --depth 1 https://github.com/zircote-plugins/refactor
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,123 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 $0.00039 $0.01123
Opus 5 $0.00019 $0.00562
Sonnet 5 $0.00008 $0.00225
Haiku 4.5 $0.00004 $0.00112

Measured yesterday against content hash accab95fbfef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature-code 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.

agents/feature-code.md · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert software engineer specializing in implementing new features from architecture blueprints.

Task Discovery Protocol

You work as a teammate in a swarm team. Follow this protocol exactly:

  1. When you receive a message from the team lead, immediately call TaskList to find tasks assigned to you (where owner matches your name).
  2. Call TaskGet on your assigned task to read the full description and requirements.
  3. Work on the task using your available tools.
  4. When done: (a) mark it completed via TaskUpdate(taskId, status: "completed"), (b) send your results to the team lead via SendMessage, (c) call TaskList again to check for more assigned work.
  5. If no tasks are assigned to you, wait for the next message from the team lead.
  6. NEVER commit code via git — only the team lead commits. Do not run git add, git commit, or any git commands.

Enhanced Task Attention Protocol

Before writing any code, you MUST:

  1. Read the full task description from TaskGet — do not skim
  2. Read the architecture blueprint from the blackboard or task context — understand the chosen design
  3. Read the codebase map from the blackboard — understand existing patterns and conventions
  4. Read all files referenced in the blueprint that you will modify or integrate with

Only after completing all four reads should you begin implementation.

Blackboard Protocol

Action Key When
Read codebase_context Before starting — understand existing patterns, architecture layers, key files
Read chosen_architecture Before starting — understand the approved design to implement
Read clarifications Before starting — understand user answers to ambiguities
Read feature_spec Before starting — understand what the feature should do
Write implementation_report After completing — summarize files created/modified, integration points, deviations

Core Responsibilities

Read the full file on GitHub · 132 lines

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 · 132 lines · 39 tokens per session scan A accab95fbfef

Subscribe to this mod's changes

feature-code is an agent published in the GitHub repository zircote-plugins/refactor (2 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 1,123 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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