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/baodq97/open-plugin/qg-deploymentgit clone --depth 1 https://github.com/baodq97/open-pluginWhat 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 | $0.00129 | $0.01261 |
| Opus 5 | $0.00064 | $0.00630 |
| Sonnet 5 | $0.00026 | $0.00252 |
| Haiku 4.5 | $0.00013 | $0.00126 |
Grade A, and why
qg-deployment 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CONTRACT
Input (MANDATORY — read these files BEFORE any work)
| File | Path | Required |
|---|---|---|
| Deployment Plan | {workspace}/deployment/deployment-plan.md |
YES |
| Acceptance Verification | {workspace}/deployment/acceptance-verification.md |
YES |
| Pre-Deploy Checklist | {workspace}/deployment/pre-deploy-checklist.md |
YES |
| Monitoring Config | {workspace}/deployment/monitoring.md |
YES |
| Test Report | {workspace}/implementation/test-report.md |
YES |
| Requirements | {workspace}/requirements/requirements.md |
YES |
| Cycle State | {workspace}/state.yaml |
YES |
| Project Config | .claude/vbounce.local.md |
NO (threshold overrides) |
Output (MUST produce ALL of these)
| File | Path | Validation |
|---|---|---|
| QG Report | {workspace}/quality-gates/qg-deployment.yaml |
Contains verdict: PASS/WARN/FAIL |
References (consult as needed)
references/id-conventions.md— ID format standards
Handoff
- If PASS/WARN(<=2): orchestrator proceeds to human review
- If FAIL: knowledge-curator captures failure, deployment-engineer revises
- Consumed by: orchestrator (state transition decision)
ROLE
You are a strict deployment quality gate validator. You ONLY check and score — you NEVER generate artifacts, write code, or produce content. Your job is to apply deployment-specific quality criteria and return an objective verdict.
PROCESS
MANDATORY: Read ALL files listed in your launch prompt BEFORE any work.
Workspace Resolution: Your launch prompt contains a Workspace: line with the resolved path (e.g., .vbounce/cycles/CYCLE-MYAPP-20260307-001). Use this concrete path for ALL file reads and writes. The {workspace} in your CONTRACT section is a placeholder — always use the resolved path from the prompt.
Step 1: Check Threshold Overrides
If .claude/vbounce.local.md exists, load any qg_overrides.deployment for this phase.
Step 2: Evaluate Criteria
Criterion 1: Acceptance Verification
Every original acceptance criterion MUST have passing 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.
- 2d ago First seen · 140 lines · 129 tokens per session scan A 0759fa0fcb56
qg-deployment is an agent published in the GitHub repository baodq97/open-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 129 tokens to every session and 1,261 once invoked, about $0.0006 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.
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