pairwise

A tool for building pairwise test plans when several independent factors—such as browser, operating system, or network mode—have different numbers of possible values. It lists a small set of runs covering every pair of values.

In plain words
What is it for?
Use it to create debugging or testing run sheets for mixed factor values, especially when fixed test arrays do not fit.
Why use it?
It helps expose bugs caused by interactions between two factors without testing every possible combination.

Skill for Claude CodeCodex

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 skills/lexfrei/ccc/pairwise
Any agent
npx skills add lexfrei/ccc --skill pairwise
Clone the repo
git clone --depth 1 https://github.com/lexfrei/ccc

Made for: Claude Code, Codex.

Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 874 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 $0.00130 $0.00874
Opus 5 $0.00065 $0.00437
Sonnet 5 $0.00026 $0.00175
Haiku 4.5 $0.00013 $0.00087

Measured 2d ago against content hash 510014c4b0a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pairwise 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.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/pairwise.py, scripts/test_pairwise.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/doe/skills/pairwise/SKILL.md · 47 lines

How it starts

The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.

A pairwise covering array guarantees every combination of levels of every factor pair appears in at least one run, in close to the minimal number of runs. Any behavior driven by one factor or a two-factor interaction is guaranteed to fire somewhere in the array — that is the same trigger guarantee the taguchi arrays give, without their fixed 2-3-level shapes.

The tradeoff: covering arrays are not balanced. Levels appear unequal numbers of times, so averaging outcomes per level is not a fair comparison between factors. Use this skill to make the bug fire and to shortlist suspects; rank and confirm with balanced follow-ups.

Step 1 — factors and levels

Same rules as the taguchi skill: factors must be independently settable, every level discrete and articulable, observable-but-unsettable factors recorded as covariates. Level counts are unrestricted — that is the point of this skill.

Step 2 — generate the run sheet

Run the bundled generator (relative to this skill's base directory):

python3 scripts/pairwise.py "net=fast,slow,flaky,off" "browser=chrome,firefox,safari" "os=linux,macos"

It prints a markdown run sheet plus the run count against the full factorial. The output is self-verified: the script crashes rather than print an array with an uncovered pair. It restarts the greedy search from 64 seeds and keeps the shortest array — the seeds cost milliseconds, the runs they save cost CI round-trips (--restarts trades one for the other, --json emits the rows for a driver script).

Combinations that cannot be run go in as constraints, not as rows you quietly skip. Safari does not run on Linux; version X does not build against Y. Dropping such a row by hand takes its pairs down with it and the coverage guarantee is gone without a word:

python3 scripts/pairwise.py "browser=chrome,firefox,safari" "os=linux,macos" "net=fast,slow" \
    --exclude "browser=safari & os=linux"

Excluded rows are never generated, pairs that no legal row can contain leave the target set, and everything still reachable stays covered.

Read the full file on GitHub · 47 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 47 lines · 130 tokens per session scan A 510014c4b0a9

Subscribe to this mod's changes

pairwise is a skill published in the GitHub repository lexfrei/ccc (9 stars, last pushed 2d ago), licensed BSD-3-Clause. It adds 130 tokens to every session and 874 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 2026-08-31.

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