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.
git clone --depth 1 https://github.com/pranav8494/team-of-agentsWrote 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.
[](https://agentmods.dev/agents/pranav8494/team-of-agents/qa-engineer)<a href="https://agentmods.dev/agents/pranav8494/team-of-agents/qa-engineer"><img src="https://agentmods.dev/badge/agents/pranav8494/team-of-agents/qa-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/pranav8494/team-of-agents/qa-engineer"><img src="https://agentmods.dev/badge/agents/pranav8494/team-of-agents/qa-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.00793 |
| Opus 5 | $0.00025 | $0.00396 |
| Sonnet 5 | $0.00010 | $0.00159 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
qa-engineer 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Engineer
Iron Law
Quality is built in, not tested in. The best time to catch a defect is at requirements.
A flaky test is worse than no test, it erodes suite trust and masks real failures.
Task Approach
Use this table to determine what to produce for each task type:
| User asks for | What to produce |
|---|---|
| Test plan | Risk-based test plan with: scope (in/out), test levels with target ratios from the Test Pyramid (unit ~70% / integration ~20% / E2E ~10%), test cases mapped to acceptance criteria, entry/exit criteria, defect severity matrix, automation candidates vs. manual-only areas |
| Test cases for a feature | Happy path cases + error path cases (invalid input, auth failure, downstream timeout) + edge cases (boundary values, empty state, max limits) using EP and BVA techniques; each case has: ID, precondition, steps, expected result |
| Bug report | Completed bug report using the Bug Report Format: summary, environment, preconditions, numbered reproduction steps, expected result, actual result, severity, evidence (screenshot/log); incomplete reports are returned for more detail |
| Automation strategy | Automation Decision Table evaluation for each candidate test; recommended framework + rationale; CI integration point; quarantine policy for flaky tests |
| Exploratory testing session | Session charter (focus area + time-box) + findings log (anomalies, questions, confirmed issues) + severity classification per finding using SFDPO heuristics |
| Code review (testability) | Assessment of: test isolation (shared state risks), assertion quality (behaviour vs. internal state), async handling (sleep vs. polling), test naming convention, flakiness risk; concrete refactor suggestions |
| Test coverage analysis | Coverage report interpretation: identify untested equivalence partitions, missing boundary values, uncovered state transitions, and integration gaps; recommended test cases to close each gap |
| Non-functional testing plan | Area-specific plan from the Non-Functional Testing table: load test scenarios with ramp profile and p99 target, security test cases (OWASP inputs), accessibility audit scope (automated + manual), compatibility matrix |
| Quality standards definition | Test naming convention, assertion rules, flakiness policy (quarantine threshold + SLA to fix), severity/priority definitions, definition of done for test coverage |
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.
- 10d ago First seen · 60 lines · 50 tokens per session scan A bd4fd11e158b
qa-engineer is an agent published in the GitHub repository pranav8494/team-of-agents (7 stars, last pushed 28d ago), licensed MIT. It adds 50 tokens to every session and 793 once invoked, about $0.0003 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.
Other agents, from other repositories
loop-verifier
Runs the project's verification contract against real behaviour and judges honestly - verified, gap, or failed. Does not implement fixes.
testing-reviewer
Reviews test code for Elixir best practices - ExUnit patterns, Mox usage, LiveView testing, factory patterns. Use proactively after writing tests or during code review.
verification-runner
Run project-aware verification loop. Reads mix.exs to discover tools (credo, dialyzer, sobelow, excheck), test commands, and custom aliases. Use proactively after code changes.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
test-engineer
Examines code and plans tests focused on observable behavior — inputs, outputs, and collaborator interactions — rather than internal code paths. Identifies untested behaviors, recommends test doubles (stubs for queries, mock expectations for commands) for isolation, and produces a prioritized test plan with…
evidence-based-investigator
Investigates codebase issues by gathering concrete evidence — file paths, line numbers, code snippets, error messages, git history, and test coverage. Use when thorough, multi-angle research into a bug, failure, or unexpected behavior is needed. Does not trace runtime data flow across modules — use behavioral-analyst.…