A command for answering data questions, from simple lookups to multi-step analysis and formal reports.

Use it for metrics, filters, trend analysis, comparisons, and data reports when a connected data warehouse is available.

It provides a workflow for clarifying the question, finding the needed data, querying it, and presenting the result.

analyze — Command by fergupa

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/fergupa/claude_plugins/analyze

Clone the repo

git clone --depth 1 https://github.com/fergupa/claude_plugins

Or install data, the plugin that ships this one along with the rest of its 7 skills, 6 commands.

Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 921 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.

Model	Per session	Once invoked
Fable 5	$0.00011	$0.00921
Opus 5	$0.00005	$0.00461
Sonnet 5	$0.00002	$0.00184
Haiku 4.5	$0.00001	$0.00092

Measured 2d ago against content hash b8bac8b88a18, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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.

data/commands/analyze.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/analyze - Answer Data Questions

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Answer a data question, from a quick lookup to a full analysis to a formal report.

Usage

/analyze <natural language question>

Workflow

1. Understand the Question

Parse the user's question and determine:

Complexity level:
- Quick answer: Single metric, simple filter, factual lookup (e.g., "How many users signed up last week?")
- Full analysis: Multi-dimensional exploration, trend analysis, comparison (e.g., "What's driving the drop in conversion rate?")
- Formal report: Comprehensive investigation with methodology, caveats, and recommendations (e.g., "Prepare a quarterly business review of our subscription metrics")
Data requirements: Which tables, metrics, dimensions, and time ranges are needed
Output format: Number, table, chart, narrative, or combination

2. Gather Data

If a data warehouse MCP server is connected:

Explore the schema to find relevant tables and columns
Write SQL query(ies) to extract the needed data
Execute the query and retrieve results
If the query fails, debug and retry (check column names, table references, syntax for the specific dialect)
If results look unexpected, run sanity checks before proceeding

If no data warehouse is connected:

Ask the user to provide data in one of these ways:
- Paste query results directly
- Upload a CSV or Excel file
- Describe the schema so you can write queries for them to run
If writing queries for manual execution, use the sql-queries skill for dialect-specific best practices
Once data is provided, proceed with analysis

3. Analyze

Calculate relevant metrics, aggregations, and comparisons
Identify patterns, trends, outliers, and anomalies
Compare across dimensions (time periods, segments, categories)
For complex analyses, break the problem into sub-questions and address each

Read the full file on GitHub · 119 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.

2d ago First seen · 119 lines · 11 tokens per session scan A b8bac8b88a18

Subscribe to this mod's changes

analyze is a command published in the GitHub repository fergupa/claude_plugins (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 921 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.

Analytics and metrics

analyze