Borrowing it
Nothing to install: this file belongs to LedgerHQ/ledger-live. 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/LedgerHQ/ledger-live/develop/.agents/skills/feature-dev/SKILL.mdgit clone --depth 1 https://github.com/LedgerHQ/ledger-liveWrote 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/skills/ledgerhq/ledger-live/feature-dev)<a href="https://agentmods.dev/skills/ledgerhq/ledger-live/feature-dev"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/feature-dev/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/skills/ledgerhq/ledger-live/feature-dev"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/feature-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 18 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00014 | $0.01162 |
| Opus 5.5 | $0.00006 | $0.00465 |
| Sonnet 5.5 | $0.00003 | $0.00232 |
| Haiku 4.5 | $0.00001 | $0.00116 |
Grade A, and why
feature-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 29d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- feature-dev — 86% identical, 66 lines differ
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description: Guided feature development with codebase understanding and architecture focus argument-hint: Optional feature description
Feature Development
You are helping a developer implement a new feature for Ledger Wallet applications. Follow a systematic approach: understand the codebase deeply, identify and ask about all underspecified details, design elegant architectures, then implement.
References
New features must be implemented in src/mvvm/ following the MVVM architecture (.agents/skills/mvvm-architecture/SKILL.md).
Shared logic extracted out of an app goes to shared/, domain/ or features/, not to libs/.
Core Principles
- Ask clarifying questions: Identify all ambiguities, edge cases, and underspecified behaviors. Ask specific, concrete questions rather than making assumptions. Wait for user answers before proceeding with implementation. Ask questions early (after understanding the codebase, before designing architecture).
- Understand before acting: Read and comprehend existing code patterns first
- Read files identified by agents: When launching agents, ask them to return lists of the most important files to read. After agents complete, read those files to build detailed context before proceeding.
- Simple and elegant: Prioritize readable, maintainable, architecturally sound code
- Use TodoWrite: Track all progress throughout
Phase 1: Discovery
Goal: Understand what needs to be built
Initial request: $ARGUMENTS
Actions:
- Create todo list with all phases
- If feature unclear, ask user for:
- What problem are they solving?
- What should the feature do?
- Any constraints or requirements?
- Summarize understanding and confirm with user
Phase 2: Codebase Exploration
Goal: Understand relevant existing code and patterns at both high and low levels
Actions:
- Launch 2-3 code-explorer agents in parallel. Each agent should:
- Trace through the code comprehensively and focus on getting a comprehensive understanding of abstractions, architecture and flow of control
- Target a different aspect of the codebase (eg. similar features, high level understanding, architectural understanding, user experience, etc)
- Include a list of 5-10 key files to read
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.
- 29d ago Changed 2b0122ea6c22
- 1mo ago Changed 2693d1452faa
- 1mo ago First seen · 136 lines · 14 tokens per session scan A afebedd194d6
feature-dev is a skill published in the GitHub repository LedgerHQ/ledger-live (625 stars, last pushed today), licensed MIT. It adds 14 tokens to every session and 1,162 once invoked, about $0.0001 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 2026-08-30.
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