write-tests

A method for writing software tests around observable behavior rather than internal code details. It uses test-driven development (TDD): write one test, see it fail, then change the code until it passes.

In plain words
What is it for?
For adding tests for new behavior, regression fixes, refactors, configuration changes, and brittle or flaky test suites.
Why use it?
It reduces tests that pass by luck or break during harmless refactoring, and checks that each test can detect a real failure.

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/dzhng/duet-agent/write-tests
Any agent
npx skills add dzhng/duet-agent --skill write-tests
Clone the repo
git clone --depth 1 https://github.com/dzhng/duet-agent

Made for: Claude Code, Codex.

Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,727 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00063 $0.01727
Opus 5 $0.00032 $0.00864
Sonnet 5 $0.00013 $0.00345
Haiku 4.5 $0.00006 $0.00173

Measured 3d ago against content hash 8c19362fbb8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

write-tests 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 3d 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.

Origin

This is a copy

100% identical to write-tests — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/write-tests/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Write Tests

A good test fails only when real behavior breaks, and passes through every refactor or config change that preserves it. Most bad tests fail the opposite way: red on harmless changes, green while the real path is broken. Every rule below serves that one goal.

Workflow: tracer bullets, not a batch

  1. Write ONE test at a time. Assert first, watch it go red on the un-fixed code, make the code earn green, learn, then write the next. Never a batch up front: a batch written against imagined behavior pins what you guessed — those tests pass when the mechanism breaks and fail when it's fine. Each green cycle tells you what the next test should actually assert.
  2. Iterate on the fastest focused runner (one file, one test name), and run the full suite only as a final gate before handing off. Check the exit code, not just the output — a runner that prints nothing and a green run look the same. On failures, read EVERY red test before fixing one; they often share a root cause.
  3. Before calling it done, prove the test can fail (below) and walk the review checklist.

What to assert

  • Observable behavior through the outermost practical entry point — return values, exit codes, persisted rows, HTTP responses, rendered output — never which internal functions ran or how a value is computed. A test on the public surface survives a rewrite of everything underneath; a test that reaches into internals breaks on every refactor and pins implementation, not behavior. Reserve isolated unit tests for genuinely tricky pure logic (parsers, schedulers, state machines).
  • Nothing the compiler already guarantees. A test that re-asserts a type signature — field shapes, rejected argument types — can only fail if the compiler failed first. Spend the budget on business rules, arithmetic, branching, ordering, edge cases, side effects.
  • Actual values, not collection sizes. For dedup/normalize/idempotency paths, length == 1 passes even when normalization is broken; also assert the stored value equals the expected canonical form.
  • The smallest scale that can show the behavior. Two entities and one mechanism before crowds and integration; small tests fail fast with readable state and don't entangle five behaviors in one assert.
  • The design contract, not current behavior. When a test goes red, the reflex is to re-measure and pin the new number — resist it: a bar calibrated to whatever the code currently does silently encodes bugs as baseline. Write the assert from the stated contract and make the code earn it; if no contract exists, that's a question for the owner, not a number to measure-and-pin. Recalibrating is legitimate only when the contract itself changed.
  • Deterministic claims tight, stochastic claims as distributions. An invariant that holds every run gets an exact threshold. Anything noisy or tuning-dependent ("A usually beats B", "load balances evenly") must be asserted over a set of runs/seeds as a band — a single-sample pin on a stochastic outcome is not a weak test, it is a blind one: it certifies whatever the lucky sample did and can mask a systematic bias for months. If you must assert a noisy differential, widen the margin and name it chaos-marginal in a comment.

Read the full file on GitHub · 134 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. 3d ago First seen · 134 lines · 63 tokens per session scan A 8c19362fbb8a

Subscribe to this mod's changes

write-tests is a skill published in the GitHub repository dzhng/duet-agent (42 stars, last pushed 3d ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,727 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to write-tests, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories