The original listing named Mock-Agent-Tester and linked to github.com/mock/agent-tester. On 2026-08-21, that repository returned 404 through GitHub’s API, and an exact-name repository search returned no result. We could not connect this name to an owner, package registry, release, license, documentation, or security contact.
Earlier claims about fast routing, extensible skills, Reddit sentiment, and Windows support have been removed because their sources could not be verified. The external button now opens a GitHub verification search; it is not an official product website. The page remains online as a transparent correction and a route to supported alternatives.
What could be verified
| Check | Result | Editorial consequence |
|---|---|---|
| Listed repository | GitHub API returned 404 | No source tree, owner, issues, or commits can be inspected |
| Exact-name search | No repository result | No canonical replacement could be attributed |
| Package or release | None attributable | No installable artifact or checksum can be verified |
| License | Not found | Usage, modification, and redistribution rights are unknown |
| Previous claims | No traceable evidence | Routing, skills, Reddit, and Windows claims were withdrawn |
What “unverified” means
A 404 does not establish why a repository is unavailable. It may have been renamed, transferred, made private, or deleted. The narrower and defensible conclusion is that the current listing does not provide enough evidence to verify the project’s present code, maintenance, compatibility, or license.
Unverified is a statement about available evidence, not an accusation about the project or its author. This page therefore makes no claim about installation, features, compatibility, open-source status, maintenance, or security. If an attributable canonical source appears, the status should be reviewed again.
Evidence required to restore a product review
- Provide an owner-controlled domain or organization profile.
- Provide the canonical repository and an attributable maintainer identity.
- Provide a license file and current documentation.
- Provide the latest release or commit plus an installable artifact and checksum.
- Provide a security contact and, where relevant, privacy or data-handling terms.
- Re-run capability claims against reproducible examples before restoring a product rating.
A practical agent-testing baseline
The following is independent editorial guidance, not a feature list for Mock-Agent-Tester. Teams that need to test agents today should cover behavior, state changes, failure paths, and permissions—not only the final answer.
| Layer | Evidence to collect | Recommended method |
|---|---|---|
| Identity | Owner, repository, release, license, checksum | Before running any code |
| Tool behavior | Selected tool, arguments, permissions, side effects | Deterministic assertions |
| Failure handling | Timeout, malformed response, denial, retry, partial success | Mocks plus sandbox contracts |
| Answer quality | Correctness, evidence, clarification, refusal | Human labels and calibrated graders |
| Safety | Injection, secret leakage, excessive agency | Least privilege and approval gates |
| Operations | Latency, cost, step count, repeatability | Repeated runs and versioned traces |
Mocks make failures reproducible but cannot reproduce every provider, browser, network, or production behavior. Pair fast deterministic tests with sandbox contract tests and a small, guarded end-to-end suite. Use an LLM judge only for criteria that code cannot express, and calibrate it against human-labeled examples.
Supported alternatives
| Option | Best fit | Main trade-off |
|---|---|---|
| Promptfoo | Local/CI prompt and model matrices, assertions, red teaming | Teams must govern providers, fixtures, and evaluator choices |
| LangSmith evaluations | Traced datasets, offline and online evaluation, human/code/LLM graders | Hosted data governance and pricing require review |
| OpenAI hosted Evals | OpenAI-centered datasets, criteria, asynchronous runs, and reports | Closer platform coupling and API cost |
| OpenAI Evals repository | Open-source evaluation patterns and custom eval code | Different path from the current hosted Evals product |
| Custom test doubles | Exact control of state, permissions, clocks, failures, and side effects | Highest engineering effort; strongest for business rules |
Independent judgment: do not select or reject a tool from a name alone. For a production agent, a hybrid stack is usually stronger than a single evaluation product: deterministic state assertions for irreversible behavior, plus a supported semantic-evaluation platform for answer quality and regression analysis.
Limits and safety notes
No benchmark or hands-on product result can be reported because no executable project was verified. The comparison above describes the cited alternatives, not Mock-Agent-Tester.
Agent test datasets may contain private prompts, retrieved documents, customer records, and tool outputs. Review retention, training use, regions, subprocessors, access controls, and deletion before sending traces to a hosted evaluator.
Prompt injection can arrive through user input or retrieved content. Tests should assert tool permissions and state transitions so that unsafe actions remain blocked even when the model produces persuasive text.
Frequently asked questions
Is Mock-Agent-Tester a confirmed software project?
Not from the evidence currently available. The listed repository returned 404 and no exact-name replacement could be attributed on August 21, 2026.
What can be concluded from the 404?
The current URL cannot establish the project’s present status. A rename, transfer, private setting, or deletion remains possible.
Can I install it?
No official package or release could be verified, so this page does not provide an installation command.
Is it open source?
Unknown. No attributable license file or canonical source repository was found.
Why keep this page?
It preserves a transparent correction for users who encounter the old listing and explains what evidence is still missing.
What should I use for agent evaluation now?
Consider Promptfoo for portable CI matrices, LangSmith for traced evaluation workflows, OpenAI hosted Evals for OpenAI-centered systems, and custom deterministic tests for permissions and side effects.
Sources checked
- Repository URL stored in the original listing
- GitHub repository API verification endpoint
- Exact-name GitHub repository search
- Promptfoo evaluation documentation
- Promptfoo repository and license
- LangSmith evaluation concepts
- OpenAI hosted Evals guide
- OpenAI Evals repository
- OWASP prompt-injection guidance
Evidence reviewed independently on 2026-08-21. Recheck the status if a canonical owner or repository is supplied.
