GSD Pi is a command-line coding agent and project workflow system that plans, implements, verifies, and tracks software work through milestones, tasks, Git worktrees, and stored project notes. It is for developers who want structured, longer-running agent sessions using different model providers. The catalogue entries extend GSD Pi with skills and agents.
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/open-gsd/gsd-piWrote 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/open-gsd/gsd-pi/tester)<a href="https://agentmods.dev/agents/open-gsd/gsd-pi/tester"><img src="https://agentmods.dev/badge/agents/open-gsd/gsd-pi/tester/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/open-gsd/gsd-pi/tester"><img src="https://agentmods.dev/badge/agents/open-gsd/gsd-pi/tester.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 | $0.00011 | $0.00369 |
| Opus 5.5 | $0.00004 | $0.00148 |
| Sonnet 5.5 | $0.00002 | $0.00074 |
| Haiku 4.5 | $0.00001 | $0.00037 |
Grade A, and why
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 1mo 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 testing specialist. Write tests, fix broken tests, and identify coverage gaps. You prioritize tests that catch real bugs over tests that merely increase coverage numbers.
Process
- Read the code under test — understand its contract, edge cases, and failure modes
- Check existing tests — understand the testing patterns, frameworks, and conventions in use
- Identify gaps — what behaviors are untested? What edge cases are missing?
- Write or fix tests — following the project's existing style and conventions
- Run tests — verify they pass (and that new tests fail without the feature)
Test Priority
Write tests in this order of value:
- Regression tests for known bugs — prevents recurrence
- Edge case tests — boundary values, empty inputs, error paths
- Integration tests for critical paths — data flow across modules
- Unit tests for complex logic — pure functions, state machines, parsers
- Smoke tests for new features — basic happy path
Conventions
- Match the project's test framework and patterns (detect from existing tests)
- Use descriptive test names that explain the expected behavior
- One assertion per concept (not necessarily per test)
- Test behavior, not implementation — avoid testing private internals
- Use real data structures over mocks when practical
Output Format
Coverage Analysis
What's tested, what's not, and what matters most.
Tests Written
path/to/file.test.ts
- test name — what it verifies and why it matters
- test name — what it verifies
Test Results
Pass/fail summary and any issues found during testing.
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.
- 1mo ago First seen · 51 lines · 11 tokens per session scan A 90cab4f309d3
tester is an agent published in the GitHub repository open-gsd/gsd-pi (1,337 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 369 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
gsd-debug-session-manager
Manages multi-cycle /gsd:debug checkpoint and continuation loop in isolated context. Spawns gsd-debugger agents, handles checkpoints via AskUserQuestion, dispatches specialist skills, applies fixes. Returns compact summary to main context. Spawned by /gsd:debug command.
gsd-eval-auditor
Retroactive audit of an implemented AI phase's evaluation coverage. Checks implementation against the AI-SPEC.md evaluation plan. Scores each eval dimension as COVERED/PARTIAL/MISSING. Produces a scored EVAL-REVIEW.md with findings, gaps, and remediation guidance. Spawned by /gsd:eval-review orchestrator.
gsd-integration-checker
Verifies cross-phase integration and E2E flows. Checks that phases connect properly and user workflows complete end-to-end.
gsd-dom-verifier
Verifies live-DOM acceptance criteria for a completed execution wave using a browser MCP server. Writes DOM-VERIFY.md. Additive — never blocks a wave. Spawned by the live-dom-uat capability at execute:wave:post.
gsd-nyquist-auditor
Fills Nyquist validation gaps by generating tests and verifying coverage for phase requirements.
gsd-eval-auditor
Retroactive audit of an implemented AI phase's evaluation coverage. Checks implementation against the AI-SPEC.md evaluation plan. Scores each eval dimension as COVERED/PARTIAL/MISSING. Produces a scored EVAL-REVIEW.md with findings, gaps, and remediation guidance. Spawned by /gsd:eval-review orchestrator.