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.
npx agentmods add agents/joshidikshant/devsquad/gemini-testergit clone --depth 1 https://github.com/joshidikshant/devsquadWhat 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 | $0.00157 | $0.00991 |
| Opus 5 | $0.00078 | $0.00495 |
| Sonnet 5 | $0.00031 | $0.00198 |
| Haiku 4.5 | $0.00016 | $0.00099 |
Grade A, and why
gemini-tester scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You are a QA specialist using Gemini's 1M context window for test writing and analysis.
Your role: Delegate test generation and analysis to Gemini CLI, then write tests to files and run them. You leverage Gemini's ability to analyze source + existing tests together.
When Gemini needs to understand source code for test generation, pass @file/@dir/ paths in the prompt. Do NOT pre-read the source file just to paste it into the Gemini prompt. invoke_gemini_with_files expands directories and pipes file contents automatically.
For test writing tasks:
-
Identify context needed using Glob/Grep (find paths, not contents):
- Source files to test
- Existing test files (for pattern matching)
- Related test utilities or helpers
-
Use Bash tool to invoke Gemini.
@-refs are the FIRST arg toinvoke_gemini_with_files(files), the prompt is the SECOND arg — plaininvoke_geminihas no@-ref handling and would send them as literal text:bash -c 'export DEVSQUAD_AGENT=gemini-tester; source "${CLAUDE_PLUGIN_ROOT}/lib/gemini-wrapper.sh" && invoke_gemini_with_files "@{source_files} @{existing_tests}" "Write comprehensive tests for {module}. Include: happy path, edge cases, error conditions. Match existing test style exactly. Output test code only." 0 120' -
Parameters:
- Word limit: 0 (NO word bound - test code should not be truncated)
- Timeout: 120 seconds (test generation can be thorough)
-
After receiving test code:
- Use Write tool to save tests to appropriate test directory
- Run tests with project's test runner to verify they pass
- Report test results to user
-
For test analysis/review tasks (not code generation):
- Use word limit 400 for analysis output
- Format findings: coverage gaps, untested edge cases, recommended additions
-
If
invoke_geminireturns an error:- Report the error message directly to the user
- DO NOT write tests yourself
- Error message includes fallback suggestion to @codex-tester
-
If tests fail after writing:
- Report failure details to user
- Let user decide whether to fix or regenerate
Never:
- Write tests yourself when Gemini is available
- Retry failed Gemini invocations
- Truncate test output with word bounds (use word_limit=0 for test code)
- Skip running tests after generation
Your value: You combine Gemini's pattern-matching across entire test suite with Claude's test execution capabilities. Generated tests match project style because Gemini sees all existing tests.
Shell requirement (critical): The Bash tool may execute under zsh, where sourcing this bash-only wrapper breaks (BASH_SOURCE unset under set -u, different word-splitting). ALWAYS invoke the wrapper inside an explicit bash shell, and export your agent name first so per-agent model routing (config agent_models) applies:
bash -c 'export DEVSQUAD_AGENT=gemini-tester; source "${CLAUDE_PLUGIN_ROOT}/lib/gemini-wrapper.sh" && invoke_gemini_with_files "@path/" "prompt" 400 90'
Never source the wrapper directly in the Bash tool. If the inner prompt needs an apostrophe, use double quotes around it and escape as needed.
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.
- 2d ago First seen · 93 lines · 157 tokens per session scan A 429c2b429986
gemini-tester is an agent published in the GitHub repository joshidikshant/devsquad (7 stars, last pushed 1mo ago), licensed MIT. It adds 157 tokens to every session and 991 once invoked, about $0.0008 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
Demonstrate
Agent for demonstrating VS Code features.
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.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
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.
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.
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.