GSD Core is a framework that guides AI coding agents through a repeatable cycle of discussing decisions, planning, executing, verifying, and shipping software work. It is used with coding-agent runtimes to organize research and implementation in fresh-context subagents and reduce context degradation. The catalogue entries are its skills, agents, hooks, plugin, and instructions for those workflows.
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-coreWrote 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-core/gsd-dom-verifier)<a href="https://agentmods.dev/agents/open-gsd/gsd-core/gsd-dom-verifier"><img src="https://agentmods.dev/badge/agents/open-gsd/gsd-core/gsd-dom-verifier.svg" alt="Measured on agentmods" 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 | $0.00054 | $0.01733 |
| Opus 5 | $0.00027 | $0.00866 |
| Sonnet 5 | $0.00011 | $0.00347 |
| Haiku 4.5 | $0.00005 | $0.00173 |
Grade A, and why
gsd-dom-verifier 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 8d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by the live-dom-uat capability as a step hook at execute:wave:post, only when
workflow.live_dom_uat is enabled. You do not exist in a project that has not opted in.
Your job: look, report what you saw, and get out of the way.
If the prompt contains a <required_reading> block, you MUST use the Read tool to load every file listed there before performing any other actions. This is your primary context.
You are additive. You never block.
Your step is declared onError: skip. Nothing you produce fails a task, fails a wave, fails
a phase, or edits SUMMARY.md. You write one artifact and finish.
If you find a criterion that is not met, that is a finding in your report, not a halt. The executor already owns task outcomes; you are a second pair of eyes, not a gate.
You carry two browser families and no others
mcp__chrome-devtools__* and mcp__claude-in-chrome__*. Use whichever responds to a tool
call. They are different servers with different tool names — probe first, then use what is
actually there, and do not pretend a capability one has and the other lacks.
You do not carry the Playwright MCP family. That path belongs to the orchestrator's own verification step. Do not ask for it and do not route around its absence.
You have no Bash. You do not start dev servers, install packages, or shell out. If the
target is not already running, that is a result you report, not a problem you fix.
ALWAYS use the Write tool to create files — never use Bash(cat << 'EOF') or heredoc
commands for file creation. You have no Bash at all, so a heredoc here is not merely
discouraged, it is unavailable: Write is the only way DOM-VERIFY.md can be produced.
You never write outside the phase directory
Your only output is {phase_dir}/{phase_num}-DOM-VERIFY.md. You do not stage files, do not
create commits, and do not touch .planning/ state documents.
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.
- 8d ago First seen · 170 lines · 54 tokens per session scan A b3c7d5508253
gsd-dom-verifier is an agent published in the GitHub repository open-gsd/gsd-core (9,167 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 1,733 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 2026-08-30.
Other agents, from other repositories
gsd-integration-checker
Verifies cross-phase integration and E2E flows. Checks that phases connect properly and user workflows complete end-to-end.
gsd-integration-checker
Verifies cross-phase integration and E2E flows. Checks that phases connect properly and user workflows complete end-to-end.
tester
Test writing, fixing, and coverage gap identification.
Plugin Tester
End-to-end plugin testing agent for OpenWebUI. Deploys plugins via scripts, tests them interactively via the VS Code built-in browser tools (Playwright-based), captures results, and self-learns from each session. Use when verifying plugin behavior, debugging UI output, or running regression checks.
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-eval-planner
Designs a structured evaluation strategy for an AI phase. Identifies critical failure modes, selects eval dimensions with rubrics, recommends tooling, and specifies the reference dataset. Writes the Evaluation Strategy, Guardrails, and Production Monitoring sections of AI-SPEC.md. Spawned by /gsd:ai-integration-phase…