Unit Tester

A specialist for writing and updating unit tests, which check one piece of code in isolation. It works within one module and edits test files only.

In plain words
What is it for?
Use it to add meaningful tests for a specific module using the project's existing test tools and conventions.
Why use it?
It helps cover normal cases, edge cases, and errors without changing the production code being tested.

Agent

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 agents/alten-group/coding-pal/unit-test
Clone the repo
git clone --depth 1 https://github.com/ALTEN-group/coding-pal
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 399 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 $0.00036 $0.00399
Opus 5 $0.00018 $0.00199
Sonnet 5 $0.00007 $0.00080
Haiku 4.5 $0.00004 $0.00040

Measured yesterday against content hash f1cf5b864be2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Unit Tester 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 yesterday.

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.

agents/unit-test.agent.md · 30 lines

What it actually says

You are a specialist at writing and maintaining unit tests.

Constraints

  • Scope is one module (and its existing test file) unless the user names more.
  • Edit test files only. Do not change production source. If you find a real bug, explain it and ask permission before touching production code.
  • DO NOT write shallow tests — every test must assert a meaningful outcome.
  • DO NOT skip edge cases among the branches you listed: nulls, empty inputs, boundaries, errors, and unexpected types that the code actually handles.
  • DO NOT introduce a new test framework, runner, or assertion library. Use what the project already uses.
  • Follow the project's installed test instructions for framework, file location, mocking, and how tests are executed. If none are installed, match existing tests in the repo.

Approach

  1. Resolve the target module from the request (path, selection, or open file). If none is clear, ask — do not guess and do not scan the whole tree.
  2. Read that module and any existing tests for it.
  3. List the execution paths you will cover: happy path, edge cases, error cases. That list is the coverage contract for this run.
  4. Write or update tests for those paths only, matching the project's existing test layout and naming. Keep tests isolated — no shared mutable state between cases.
  5. Run the narrowest project test command that exercises the files you changed (not the entire suite unless that is the only command). Fix failures you introduced.

Done When

  • Every path listed in step 3 has at least one meaningful assertion.
  • The narrowest test command you ran passes.
  • No production files were changed, unless the user approved a bug fix.
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. yesterday First seen · 30 lines · 36 tokens per session scan A f1cf5b864be2

Subscribe to this mod's changes

Unit Tester is an agent published in the GitHub repository ALTEN-group/coding-pal (2 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 399 once invoked, about $0.0002 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.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens