always-compare

always-compare is a skill for Claude Code from ai-analyst-lab/ai-analyst-plugin. It costs 112 tokens per session (1,493 once invoked), scanned A, original, MIT.

A rule for showing every number alongside a comparison, such as an earlier period, a benchmark, or another group. It applies to rates, counts, averages, charts, and other measurements.

In plain words
What is it for?
Use it when writing analyses, reports, dashboards, chart labels, or summaries that contain measurements.
Why use it?
A number by itself does not show whether the result is good, bad, normal, or changing.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ai-analyst-plus plugin — 44 skills, 1 command, 13 agents shipped together

Good fit Use it when writing analyses, reports, dashboards, chart labels, or summaries that contain measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst-plugin/always-compare
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 ai-analyst-lab/ai-analyst-plugin --skill always-compare
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plugin

Made for: Claude Code.

Or install ai-analyst-plus, the plugin that ships this one along with the rest of its 44 skills, 1 command, 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 always-compare

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/always-compare.svg)](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/always-compare)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/always-compare"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/always-compare.svg" alt="Measured on agentmods" height="20"></a>
Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,493 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00112 $0.01493
Opus 5 $0.00056 $0.00746
Sonnet 5 $0.00022 $0.00299
Haiku 4.5 $0.00011 $0.00149

Measured 8d ago against content hash e6073d07e1a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

always-compare 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 8d 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.

ai-analyst-plus/skills/always-compare/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Always Compare

Purpose

A number alone is not an insight. "Conversion rate is 3.2%" tells the reader nothing actionable — they cannot tell if that is a crisis or a record high. This skill enforces one rule: every metric ships with a comparison.

When to Use

Before presenting ANY number to the user — in chat, in a report, in a chart caption, in a Slack message, or on a slide. This runs on every analysis output, alongside question-framing (which runs at the start; this one runs at the end).

The Rule

Never show a number alone. Anchor it to at least one comparison.

Pick the comparison that best serves the decision. In priority order:

# Comparison Type Use When Example
1 vs. prior period The question is "is this changing?" "down from 4.1% last month"
2 vs. benchmark / average The question is "is this normal?" "below the 3.8% site-wide average"
3 vs. another segment The question is "who is affected?" "vs. 5.4% on desktop"

Two comparisons beat one. A prior-period delta plus a benchmark tells the reader both the direction and the altitude. Use both when you have both.

Instructions

Step 1: Find every number in your draft output

Scan the response you are about to send. Every figure — headline stats, table cells, chart annotations, sentences in the narrative — is in scope.

Step 2: Attach a comparison to each one

For each metric, ask: compared to what? Then pull the comparison from the data:

  • Prior period: same metric, previous week / month / quarter (match the grain of the metric)
  • Benchmark: site-wide average, cohort average, target, or historical baseline
  • Segment: the same metric for a contrasting slice (mobile vs. desktop, new vs. returning, channel A vs. B)

Compute the comparison in the same query where practical — it is cheaper and less error-prone than a second round trip, and it guarantees the filters match.

Step 3: State the delta, not just both numbers

Do the subtraction for the reader. "3.2%, down from 4.1%" is better than "3.2% (last month: 4.1%)". Give direction (up/down) and magnitude (absolute points or relative %) — and be explicit about which you are using: "down 0.9pp (a 22% relative decline)".

Read the full file on GitHub · 101 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. 8d ago First seen · 101 lines · 112 tokens per session scan A e6073d07e1a8

Subscribe to this mod's changes

always-compare is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 11d ago), licensed MIT. It adds 112 tokens to every session and 1,493 once invoked, about $0.0006 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 2026-08-30.

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