dependency-opportunity-scanner

dependency-opportunity-scanner is a skill for Claude Code from bacchus-labs/wrangler. It costs 45 tokens per session (3,999 once invoked), scanned A, original, MIT.

A workflow that scans a codebase for custom code that could be replaced by maintained open-source libraries. It can implement selected refactors in an isolated worktree, add tests, and submit a pull request for review.

In plain words
What is it for?
Use it to review a project for library adoption opportunities, compare replacement options, make isolated refactors, and prepare changes for human review.
Why use it?
It helps find duplicated or unnecessary code while keeping proposed changes separate from the main working copy. The cost and benefit of each library replacement are considered before implementation.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool; mentions Claude Code.

Part of the wrangler plugin — 25 skills, 16 commands, 13 agents shipped together

Good fit Use it to review a project for library adoption opportunities, compare replacement options, make isolated refactors, and prepare changes for human review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bacchus-labs/wrangler/dependency-opportunity-scanner
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.

Any agent
npx skills add bacchus-labs/wrangler --skill dependency-opportunity-scanner
Clone the repo
git clone --depth 1 https://github.com/bacchus-labs/wrangler

Made for: Claude Code.

Or install wrangler, the plugin that ships this one along with the rest of its 25 skills, 16 commands, 13 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 dependency-opportunity-scanner

README.md
[![agentmods](https://agentmods.dev/badge/skills/bacchus-labs/wrangler/dependency-opportunity-scanner/github.svg)](https://agentmods.dev/skills/bacchus-labs/wrangler/dependency-opportunity-scanner)
Your own site
<a href="https://agentmods.dev/skills/bacchus-labs/wrangler/dependency-opportunity-scanner"><img src="https://agentmods.dev/badge/skills/bacchus-labs/wrangler/dependency-opportunity-scanner/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.

agentmods 80×15 button for dependency-opportunity-scanner

Your own site · 80×15
<a href="https://agentmods.dev/skills/bacchus-labs/wrangler/dependency-opportunity-scanner"><img src="https://agentmods.dev/badge/skills/bacchus-labs/wrangler/dependency-opportunity-scanner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,999 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00045 $0.03999
Opus 5 $0.00023 $0.01999
Sonnet 5 $0.00009 $0.00800
Haiku 4.5 $0.00005 $0.00400

Measured 10d ago against content hash c92c4fbdd442, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

dependency-opportunity-scanner 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 10d 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.

.wrangler/memory/knowledge-base/reference-prompts/skills/dependency-opportunity-scanner/SKILL.md · 616 lines

How it starts

The opening of the file, as written. The whole thing — 616 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the dependency opportunity scanner workflow coordinator. Your job is to identify code that could be simplified by adopting existing libraries, implement the refactoring in an isolated worktree, and submit a PR for human review.

Core Responsibilities

Skill Usage Announcement

MANDATORY: When using this skill, announce it at the start with:

🔧 Using Skill: dependency-opportunity-scanner | [brief purpose based on context]

Example:

🔧 Using Skill: dependency-opportunity-scanner | [Provide context-specific example of what you're doing]

This creates an audit trail showing which skills were applied during the session.

  • Scan codebase for reimplemented functionality that exists in libraries
  • Analyze cost/benefit of adopting each library
  • Create isolated git worktree for implementation
  • Implement library integration with tests
  • Submit PR with detailed rationale and impact analysis

Execution Strategy: Five-Phase Workflow

This is a workflow skill coordinating multiple phases with parallel analysis.


Phase 1: Codebase Analysis (Parallel)

Purpose: Identify patterns and custom implementations that might be library candidates.

Launch three parallel analysis agents:

Agent A: Pattern Detection

Task: Identify common patterns that libraries typically solve

Approach:

  1. Scan codebase for common patterns:
    • Date/time manipulation and formatting
    • HTTP client implementations
    • Logging and error handling utilities
    • Validation and schema checking
    • CLI argument parsing
    • Configuration management
    • Testing utilities
    • Data transformation (CSV, JSON, XML parsing)
    • Cryptographic operations
    • File system utilities
    • String manipulation helpers
    • Promise/async utilities
  2. For each pattern found:
    • Count lines of custom code
    • Assess complexity (simple wrapper vs. complex logic)
    • Identify dependencies on custom implementation
  3. Output: List of patterns with LOC and complexity ratings

Read the full file on GitHub · 616 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. 10d ago First seen · 616 lines · 45 tokens per session scan A c92c4fbdd442

Subscribe to this mod's changes

dependency-opportunity-scanner is a skill published in the GitHub repository bacchus-labs/wrangler (4 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 3,999 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.