extract-functions

extract-functions is a cursor rule for coding agents from holasoymalva/AI-Unit-Test-Builder. It costs 11 tokens per session (1,198 once invoked), scanned A, original, MIT.

A rule for finding and documenting functions in a source file so they can be tested. It records details such as function type, location, parameters, exports, and complexity.

In plain words
What is it for?
Use it to analyze source code and save a function-analysis document in the tests/analysis directory for use in unit-test generation.
Why use it?
It provides a structured inventory before unit tests are created, reducing the chance that testable functions or important cases are missed.

Cursor rule

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 rules/holasoymalva/ai-unit-test-builder/extract-functions
Clone the repo
git clone --depth 1 https://github.com/holasoymalva/AI-Unit-Test-Builder

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 extract-functions

README.md
[![agentmods](https://agentmods.dev/badge/rules/holasoymalva/ai-unit-test-builder/extract-functions.svg)](https://agentmods.dev/rules/holasoymalva/ai-unit-test-builder/extract-functions)
Your own site
<a href="https://agentmods.dev/rules/holasoymalva/ai-unit-test-builder/extract-functions"><img src="https://agentmods.dev/badge/rules/holasoymalva/ai-unit-test-builder/extract-functions.svg" alt="Measured on agentmods" height="20"></a>
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 1,198 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 $0.00011 $0.01198
Opus 5 $0.00005 $0.00599
Sonnet 5 $0.00002 $0.00240
Haiku 4.5 $0.00001 $0.00120

Measured 4d ago against content hash f43096a99ff5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

extract-functions 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 4d 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.

mdc/extract-functions.mdc · 180 lines

How it starts

The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rule: Function Extraction and Analysis

Goal

To guide an AI assistant in analyzing source code files to identify all testable functions and their characteristics. The analysis will serve as the foundation for comprehensive unit test generation.

Process

  1. Receive Source File: The user provides a specific source code file to analyze.
  2. Parse and Analyze: The AI examines the code to identify all functions, methods, and testable units.
  3. Categorize Functions: Group functions by type, complexity, and testing requirements.
  4. Generate Analysis Document: Create a structured analysis document with detailed information about each function.
  5. Save Analysis: Save the document as function-analysis-[filename].md in the /tests/analysis/ directory.

Analysis Criteria

For each identified function, extract and document:

Basic Information

  • Function Name: The exact name of the function
  • Function Type: Regular function, arrow function, class method, async function, generator, etc.
  • Location: File path and line number range
  • Export Status: Is it exported? (default export, named export, internal)

Function Signature

  • Parameters: Name, type, default values, optional parameters
  • Return Type: What the function returns (inferred or explicit)
  • Generic Parameters: Any generic type parameters

Dependencies and Context

  • External Dependencies: Imported modules, libraries, or utilities used
  • Internal Dependencies: Other functions or variables from the same file
  • Side Effects: Does the function modify external state, make API calls, manipulate DOM, etc.
  • Pure Function: Is it a pure function (same input = same output, no side effects)?

Complexity Indicators

  • Cyclomatic Complexity: Rough estimate (simple, moderate, complex)
  • Branching Logic: Number of if/else, switch, ternary operators
  • Loop Constructs: Presence of for, while, map, filter, reduce operations
  • Error Handling: Try/catch blocks, error throwing

Read the full file on GitHub · 180 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. 4d ago First seen · 180 lines · 11 tokens per session scan A f43096a99ff5

Subscribe to this mod's changes

extract-functions is a cursor rule published in the GitHub repository holasoymalva/AI-Unit-Test-Builder (7 stars, last pushed 1y ago), licensed MIT. It adds 11 tokens to every session and 1,198 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.