antithesis-feature-workload

Build a feature workload for Antithesis

Skill version: 2026-10-21 4f8d80b

Purpose and Goal

Start from a specific feature and produce a workload that tests it. Success means:

• The feature is understood well enough to identify its testable properties
• Properties are concrete and specific — invariants, reachable behaviors,

failure modes — not vague goals

• A self-driving workload exists that exercises the feature's behaviors
• Reach claims fire, proving the workload reaches the feature's important

states

• Feature invariants are checked by assertions that use the correct SDK types
• Optionally: the workload has run in Antithesis and findings have been

verified

This skill is a parallel entry point into the Antithesis workflow. Where the standard pipeline goes research → setup → workload (broad coverage), this skill goes feature analysis → targeted workload → iterate (feature focus).

Entry Points

This skill handles two starting points:

• Feature is done: Source code is available. Full analysis, full workload,

all assertions expected to pass.

• Feature is in development: Some code may exist, or just a spec or idea.

The workload includes TDD-style stubs — assertions that fail until the feature catches up. As code lands, assertions go green. The "Update workload for feature changes" workflow handles evolution.

Both entry points go through the same workflow. What varies is how many assertions pass on the first run.

Prerequisites

• A feature to test — source code, a spec, a description, or a combination
• Access to the SUT source code
• Docker Compose v2 and a container engine (Docker or Podman) for local runs
• snouty CLI 0.8.0 or newer installed when moving to Antithesis runs (not

needed for local-only work)

Relationship to Other Skills

• antithesis-research: Feature-workload performs feature-scoped analysis

— the same codebase exploration techniques narrowed to "what could go wrong with this feature" rather than "what properties does this entire system have." If full research artifacts already exist in the scratchbook, use them as context but don't require them.

• antithesis-workload: Feature-workload builds self-driving workloads, not

Test Composer commands. Assertion patterns, value menus, fault-tolerant design, and reach claims apply to both — this skill carries its own reference material adapted for feature-scoped work.

• antithesis-setup: Feature-workload does not assume Antithesis

infrastructure is or isn't set up. When the user wants to move to Antithesis and infrastructure is needed, delegate to antithesis-setup.

• antithesis-launch: Use to submit Antithesis runs. Do not run

snouty launch directly.

• antithesis-triage: Use after each Antithesis run with a focused lens:

"are the feature's properties being exercised? Any failures?" rather than a broad property portfolio review.

• antithesis-debug: Use when triage shows a property failure that needs

deeper investigation — inspect container state at the failure moment, time-travel to understand the sequence.

Definitions

• SUT: System under test.
• Feature property: A concrete, testable claim about what the feature

should do, what invariants it should maintain, or what behaviors should be reachable.

• Reach claim: A Sometimes assertion that verifies the workload actually

exercises a feature behavior. Unfired reach claims mean the workload isn't reaching the right states.

• Self-driving workload: A single program that drives the SUT, checks

invariants, and runs without external orchestration. No Test Composer.

• Dual-mode: The workload uses SDK assertions when ANTITHESIS_OUTPUT_DIR

is set (Antithesis) and equivalent local checks when it is not (local).

Documentation Grounding

Use the antithesis-documentation skill to access Antithesis docs.

• SDK reference: https://antithesis.com/docs/reference/sdk.md
• Properties and assertions: https://antithesis.com/docs/concepts/properties_assertions/assertions.md
• Fault injection: https://antithesis.com/docs/product/fault_injection.md
• Docker Compose setup: https://antithesis.com/docs/getting_started/setup_guide/docker_compose.md

Reference Files

Recommended Workflows

Design and build a feature workload

1. Read references/feature-analysis.md
2. Orient to the system: if existing research artifacts exist in

antithesis/scratchbook/, read them; otherwise build a lightweight orientation scoped to the feature's neighborhood — architecture, data flow, concurrency model

1. Understand the feature — from code, spec, conversation, or combination.

For features in development, identify what's built vs. planned

1. Discover feature properties — invariants, reachable behaviors, failure

modes. For features in development, properties for unbuilt parts become TDD-style stubs

1. Read references/faults.md to assess which fault types matter for this

feature

1. Record findings in

antithesis/feature-workloads/<feature-slug>/analysis.md

1. Read references/self-driving-workload.md
2. Read references/assertions.md
3. Read references/interesting-values.md
4. Build value menus from boundary values and configured-limit families on

the feature's code paths

1. Design and build the workload: self-driving program with dual-mode

assertions, fault tolerance, operation tracking, and reach claims for the feature's key behaviors

1. Build docker-compose for local runs (or use existing setup)
2. Run locally. Read references/iteration.md when reach claims aren't

firing or properties aren't being exercised. Iterate: check reach claims first, then adjust workload, assertions, SUT config, or properties as the evidence directs

• Reach claims not firing → adjust workload or revisit feature

understanding

• Properties not being exercised → adjust operations, values, or

assertions

• Feature understanding seems wrong → loop back to step 3

1. If moving to Antithesis:

a. Check existing setup; use antithesis-setup if infrastructure is needed b. Use antithesis-launch for runs c. Use antithesis-triage for analysis (framed: "are the feature's properties being exercised? Any failures?") d. Based on triage results: if a property failed, go to step 15; if reach claims aren't firing, go to "Iterate after a run"; if the mechanism is unclear, use antithesis-debug for deeper inspection

1. When a property fails, read references/verification.md. Classify the

finding. Any real bug found while testing a feature is valuable.

1. Document findings in

antithesis/feature-workloads/<feature-slug>/analysis.md

Iterate after a run

1. Read references/iteration.md
2. Read references/assertions.md if assertions need to change
3. Check reach claims — are feature behaviors being reached?
4. Choose iteration moves based on what you observe: workload adjustments,

assertion adjustments, SUT configuration changes, or property revision

1. Update antithesis/feature-workloads/<feature-slug>/analysis.md with what

changed, what was observed, and what to try next

Update workload for feature changes

For when the feature evolves and the workload needs to keep up:

1. Re-read the feature (what changed in the code or spec)
2. Check which properties still hold, which are new, which are obsolete
3. Update workload, assertions, and reach claims — TDD-style stubs for new

unbuilt parts, remove stubs for parts that are now built and passing

1. Re-validate locally — check reach claims, iterate as in the main

workflow's step 13 if results show gaps

General Guidance

• One feature at a time. Don't try to build workloads for multiple

features simultaneously. Each feature gets its own analysis, workload, and iteration cycle.

• Properties drive the workload. Every operation, assertion, and value

choice should connect to a discovered feature property. If work doesn't relate to a property, either discover a new property or stop.

• Reach claims are the compass. Unfired reach claims tell you the workload

isn't exercising the feature's key behaviors. Check them first on every iteration — before adjusting anything else, make sure the workload is reaching the right states.

• Local is the default starting point. Start locally unless the feature's

properties explicitly require Antithesis capabilities (fault injection, scheduling control). Local iteration is faster and gives tighter feedback loops.

• Verify before declaring victory. A property failure is a candidate, not

a confirmed bug. Read the counterexample. Understand the sequence. Confirm the mechanism. Harness bugs, assertion bugs, and workload bugs all produce property failures too.

• Record everything. The feature-workloads directory is the trail from

"we have a feature" to "we have a working workload." Future readers need to understand what properties were discovered, what was tested, and what was found.

• Design workloads to be fault-tolerant. Under Antithesis fault injection,

transient errors are expected. The workload must make progress through failures — retry with backoff, reconnect on disconnect, and track what was attempted vs what was acknowledged.

• Keep Antithesis-only code out of production paths. If you must touch

shared code for assertions, make the change surgical. SDK assertions no-op outside Antithesis, so the production cost is negligible.

• Write workload code in the project's language so it can reuse the

project's clients, helpers, and libraries.

• The workload grows with the feature. For in-development features, build

the full workload with TDD-style stubs for unbuilt parts. Assertions go green as code lands. Don't wait for completion to start testing.

Output

• antithesis/feature-workloads/<feature-slug>/analysis.md — feature

properties, codebase findings, fault assessment, iteration history

• Workload code (self-driving program with dual-mode assertions)
• docker-compose.yml for local runs (unless existing setup suffices)
• Assertions targeting feature invariants plus reach claims for feature

behaviors

Self-Review

Before declaring this skill complete, review your work against the criteria below. If your agent supports sub-agents, create a fresh-context reviewer.

Review criteria:

• System orientation was performed — enough understanding of the architecture,

data flow, and concurrency model to navigate the feature's neighborhood (or existing research artifacts were used)

• Feature properties are documented in analysis.md and connect to specific

code paths with evidence from the codebase (or to planned behavior for in-development features)

• Each property is concrete and testable — not a vague goal like "test the

feature" but a specific invariant, reachable behavior, or failure mode

• The workload exercises the feature's key behaviors (verified by reach claims

that actually fire — or, for in-development features, reach claims for built parts fire while stubs for unbuilt parts are clearly marked)

• Assertions use the correct SDK type for their semantics (Always /

AlwaysOrUnreachable for invariants, Sometimes for reach claims, Reachable for path reachability) — see references/assertions.md

• Sometimes(true, ...) assertions should be rewritten as Reachable(...)
• The workload is a self-driving program with a single entrypoint, not Test

Composer commands

• The workload is fault-tolerant — retries transient errors, makes progress

through failures, doesn't bail on the first error

• The workload tracks attempted vs acknowledged operations so assertions can

check bounds, not exact values

• The workload is dual-mode — SDK assertions when ANTITHESIS_OUTPUT_DIR is

set, local checks otherwise

• Reach claims assert the precondition, not the violation — they fire when the

system is correct

• No reach claim is the negation of an Always or AlwaysOrUnreachable at

the same site

• Value choices use boundary values and configured-limit families from the

feature's code paths, not arbitrary ranges — see references/interesting-values.md

• Assertion property names are inline constant string literals, unique across

the project — never constructed at runtime

• Randomness in the workload goes through the SDK's random module for

deterministic replay (standard library random for local mode)

• Randomness shape varies across runs (swarm testing) — probabilities and

action weights are drawn at the start of each run, not hardcoded

• Workload-only instrumentation was not used where surgical SUT-side

assertions would provide materially better search guidance for rare, dangerous, or timing-sensitive internal states

• Assertions are in workload code or surgical SUT locations — not scattered

across production paths

• If moving to Antithesis: the antithesis-setup skill was used for

infrastructure, not ad-hoc setup

• If fault types are relevant to the feature's properties: those faults are

confirmed as enabled for the tenant — see references/faults.md

• The feature-workloads directory records what was analyzed, what properties

were discovered, what was tested, and what was found at each iteration