feature-new

feature-new is a command for coding agents from RoniLeor/specWeaver. It costs 33 tokens per session (13,065 once invoked), scanned A, original, MIT.

A workflow for designing and building a new software feature with research, codebase exploration, planning, implementation phases, reviews, and documentation. It coordinates multiple agents during the process.

In plain words
What is it for?
Use it for substantial new features that need technology research, architecture decisions, detailed phase plans, parallel development, code review, testing, and updated documentation.
Why use it?
It gives a large feature a structured path from understanding the existing project to verified implementation, reducing the chance of building against the wrong assumptions.

Command

Part of the specweaver plugin — 3 commands, 5 agents shipped together

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 commands/ronileor/specweaver/feature-new
Clone the repo
git clone --depth 1 https://github.com/RoniLeor/specWeaver

Or install specweaver, the plugin that ships this one along with the rest of its 3 commands, 5 agents.

Wrote 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.

agentmods badge for feature-new

README.md
[![agentmods](https://agentmods.dev/badge/commands/ronileor/specweaver/feature-new.svg)](https://agentmods.dev/commands/ronileor/specweaver/feature-new)
Your own site
<a href="https://agentmods.dev/commands/ronileor/specweaver/feature-new"><img src="https://agentmods.dev/badge/commands/ronileor/specweaver/feature-new.svg" alt="Measured on agentmods" height="20"></a>
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 13,065 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 $0.00033 $0.13065
Opus 5 $0.00016 $0.06532
Sonnet 5 $0.00007 $0.02613
Haiku 4.5 $0.00003 $0.01307

Measured 3d ago against content hash c46e5abf4c91, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature-new 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 3d 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.

plugins/specweaver/commands/feature-new.md · 1,501 lines

How it starts

The opening of the file, as written. The whole thing — 1,501 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are orchestrating a comprehensive feature development workflow with multi-agent collaboration. Follow this structured process:

Phase 0: Codebase Exploration (Pre-Design Analysis)

IMPORTANT: This phase runs FIRST to understand the codebase context before researching solutions.

Step -1.1: Launch Parallel Research Agents

Use multiple web search tools IN PARALLEL (single message with 4 tool calls) to research:

  1. Language Best Practices (Python + TypeScript for this project):

    • Search: "Python best practices 2025 FastAPI async patterns type hints"
    • Search: "TypeScript React best practices 2025 hooks patterns"
    • Focus: Modern idioms, async/await patterns, type safety, error handling
  2. SOLID Design Principles (Keep It Simple):

    • Search: "SOLID principles practical examples Python TypeScript 2025 simple implementation"
    • Focus: Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion
    • Look for: Simple, clear implementations (avoid over-engineering), minimal complexity patterns
    • Emphasize: Simplest solution that follows SOLID, avoid premature abstraction
  3. Feature Design Patterns (Simplicity First):

    • Search: "simple software architecture patterns minimal complexity 2025"
    • Search: "KISS principle feature design patterns avoid over-engineering"
    • Focus: Minimal viable architecture, feature isolation, testability without complexity
    • Emphasize: Start simple, evolve as needed, avoid premature optimization
  4. Domain-Specific Patterns (based on $ARGUMENTS):

    • Analyze the feature description in $ARGUMENTS
    • Determine the domain (e.g., "WebSocket" → real-time communication patterns)
    • Search: "{domain} design patterns best practices 2025"
    • Focus: Domain-specific anti-patterns, proven solutions, performance considerations

Step -1.2: Synthesize Research Findings

After ALL 4 parallel searches complete, synthesize the findings:

Create: .claude/specs/new-{feature-name}/00-research.md

# Best Practices Research: {feature-name}

**Research Date**: {date}
**Feature Domain**: {domain extracted from $ARGUMENTS}

## Language Best Practices

### Python
- [Key practices found from search 1]
- [Relevant async patterns]
- [Type hint best practices]

### TypeScript/React
- [Key practices found from search 1]
- [Modern React patterns]
- [TypeScript strict mode practices]

## SOLID Design Principles Application

### Single Responsibility
- [How to apply to this feature]
- [Examples from search]

### Open/Closed Principle
- [How to design for extension]
- [Plugin/strategy patterns]

### [Other SOLID principles...]

## Feature Design Patterns

### Applicable Patterns
- [Pattern 1: description and when to use]
- [Pattern 2: description and when to use]
- [Anti-patterns to avoid]

### Modularity Considerations
- [How to isolate this feature]
- [Dependency injection points]
- [Testing strategies]

## Domain-Specific Patterns

### {Domain} Best Practices
- [Domain-specific patterns from search 4]
- [Performance considerations]
- [Security considerations]
- [Common pitfalls in this domain]

## Recommendations for {feature-name}

Based on research, this feature should:
1. [Specific recommendation 1 based on SOLID + language practices]
2. [Specific recommendation 2 based on feature patterns]
3. [Specific recommendation 3 based on domain patterns]
4. [Anti-patterns to explicitly avoid]

## References
- [Links to key resources found]

Step -1.3: Present Research Summary

Present a brief summary to the user:

 BEST PRACTICES RESEARCH COMPLETE

Researched:
 Python + TypeScript best practices (2025)
 SOLID design principles application
 Feature design patterns (modularity, testability)
 {Domain}-specific patterns and anti-patterns

Key Recommendations:
- [Top 3 recommendations for this feature]

Full research saved to: .claude/specs/new-{feature-name}/00-research.md

This research will inform the architecture design in the next phase.

Read the full file on GitHub · 1,501 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. 3d ago First seen · 1,501 lines · 33 tokens per session scan A c46e5abf4c91

Subscribe to this mod's changes

feature-new is a command published in the GitHub repository RoniLeor/specWeaver (3 stars, last pushed 10mo ago), licensed MIT. It adds 33 tokens to every session and 13,065 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.