rforge:analyze

A command for checking the health and dependencies of R packages, with separate default, debug, optimize, and release modes. R packages are reusable software libraries for the R programming language.

In plain words
What is it for?
Use it for daily health checks, dependency reviews, debugging package files and tests, investigating configuration or cache problems, and release-focused analysis.
Why use it?
It lets you choose a quick check or a deeper investigation depending on whether you need routine status, bug finding, performance work, or release preparation.

Command

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/data-wise/claude-plugins/analyze
Clone the repo
git clone --depth 1 https://github.com/Data-Wise/claude-plugins
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,464 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 $0.00015 $0.02464
Opus 5 $0.00008 $0.01232
Sonnet 5 $0.00003 $0.00493
Haiku 4.5 $0.00002 $0.00246

Measured 2d ago against content hash cf182e7b9921, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rforge:analyze 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 2d 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.

rforge/commands/analyze.md · 394 lines

How it starts

The opening of the file, as written. The whole thing — 394 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/rforge:analyze - Mode-Aware R Package Analysis

Analyze R package ecosystem with explicit control over analysis depth and performance.

Mode System

Current Mode: {{mode | default: "default"}}

Mode Selection

Parse the user's request to detect mode:

  • If user explicitly provides "debug", "optimize", or "release" → use that mode
  • Otherwise → use "default" mode (fast, balanced)

Default Mode (< 10 seconds)

Purpose: Daily check-ins, quick status validation

Behavior:

  • Focus on critical issues only
  • Recent changes (last 7 days)
  • High-priority dependencies
  • Quick health metrics
  • Balanced, actionable output

Tools: rforge_detect, rforge_status, rforge_quick_health

Time Budget: MUST complete in < 10 seconds

Output:

  • Critical issues highlighted
  • Health score
  • Next recommended action
  • Quick summary

Debug Mode (30s - 2 minutes)

Purpose: Finding bugs, investigating issues, troubleshooting

Behavior:

  • Deep inspection of all components
  • All dependencies (recursive analysis)
  • Complete file scans (R/, tests/, vignettes/)
  • Detailed error traces with stack traces
  • Hidden configuration checks
  • Cache validation
  • Environment inspection

Tools: All RForge MCP tools with detailed flags

Time Budget: SHOULD complete in < 2 minutes

Output:

  • Detailed error traces
  • Complete dependency tree
  • Per-file analysis
  • Hidden issues revealed
  • Root cause identification

Optimize Mode (1-3 minutes)

Purpose: Speed improvements, performance tuning, bottleneck detection

Behavior:

  • Profile R code execution
  • Package load time analysis
  • Dependency bloat detection
  • Function call hotspots
  • Memory usage patterns
  • Benchmark comparisons
  • Test execution time analysis

Tools: rforge_profile, performance benchmarks, load time analysis

Time Budget: SHOULD complete in < 3 minutes

Output:

  • Top 3-5 bottlenecks identified
  • Concrete optimization suggestions
  • Quantified performance impact
  • Before/after projections

Read the full file on GitHub · 394 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. 2d ago First seen · 394 lines · 15 tokens per session scan A cf182e7b9921

Subscribe to this mod's changes

rforge:analyze is a command published in the GitHub repository Data-Wise/claude-plugins (7 stars, last pushed 6d ago), licensed MIT. It adds 15 tokens to every session and 2,464 once invoked, about $0.0001 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.