testing.fix_input_output_vars

testing.fix_input_output_vars is a skill for Claude Code from causify-ai/helpers. It costs 9 tokens per session (183 once invoked), scanned A, original, Apache-2.0.

A test-refactoring guide for storing test inputs and expected outputs as indented triple-quoted strings, then comparing the complete output with an equality check. It also recommends helper functions for repeated test setup.

In plain words
What is it for?
Use it to reorganize test methods, consolidate repeated code, compare whole results instead of pieces, and verify that the tests still pass.
Why use it?
It makes tests easier to read and keeps each test focused on its intended behavior. Running the tests afterward helps confirm that the formatting changes did not alter their meaning.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; reads .claude/ paths.

Good fit Use it to reorganize test methods, consolidate repeated code, compare whole results instead of pieces, and verify that the tests still pass.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/causify-ai/helpers/testing.fix_input_output_vars
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 causify-ai/helpers --skill testing.fix_input_output_vars
Clone the repo
git clone --depth 1 https://github.com/causify-ai/helpers

Made for: Claude Code.

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 testing.fix_input_output_vars

README.md
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Your own site
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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 testing.fix_input_output_vars

Your own site · 80×15
<a href="https://agentmods.dev/skills/causify-ai/helpers/testing.fix_input_output_vars"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/testing.fix_input_output_vars.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 9 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 183 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 3
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 $0.00009 $0.00183
Opus 5.5 $0.00004 $0.00073
Sonnet 5.5 $0.00002 $0.00037
Haiku 4.5 $0.00001 $0.00018

Measured 1mo ago against content hash 51d8b14a0d48, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

testing.fix_input_output_vars 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 1mo 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.

.claude/skills/testing.fix_input_output_vars/SKILL.md · 24 lines

What it actually says

Goal

  • Transform test method so that:

    • The inputs and outputs are strings with """ and dedent
    • The output being checked with self.assert_equal()
    • Follow the directions in .claude/skills/testing.rules.md
      • # Writing Test Code
      • ## Code Formatting in Tests
      • # Test Input and Output Handling
      • ## Compare Whole Output with assert_equal, Not Piecewise
  • Factor out as much code as possible in helper functions

    • Follow the directions in .claude/skills/testing.rules.md
      • ## Use Helper Methods When You Have Repetitive Tests
  • Do not change the intent of the test

Verification

  • Run the tests to make sure that the tests are passing
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. 1mo ago Changed 51d8b14a0d48
  2. 1mo ago First seen · 24 lines · 9 tokens per session scan A 2c462b6fb169

Subscribe to this mod's changes

testing.fix_input_output_vars is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 9 tokens to every session and 183 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-03.