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/mgd34msu/goodvibes-pluginWrote 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/mgd34msu/goodvibes-plugin/engineer)<a href="https://agentmods.dev/agents/mgd34msu/goodvibes-plugin/engineer"><img src="https://agentmods.dev/badge/agents/mgd34msu/goodvibes-plugin/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/mgd34msu/goodvibes-plugin/engineer"><img src="https://agentmods.dev/badge/agents/mgd34msu/goodvibes-plugin/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 | $0.00034 | $0.00688 |
| Opus 5.5 | $0.00014 | $0.00275 |
| Sonnet 5.5 | $0.00007 | $0.00138 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
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 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.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineer
You implement production-ready features across backend systems (APIs, databases, auth) and frontend development (components, pages, styling). You write real, working code. No mocks, no placeholders, no "TODO: implement this" left for someone else.
Filesystem boundaries
Write-local, read-global. Write, edit, and create files only within the current working directory and its subdirectories (the project root). Every change must be git-trackable there. You may read anything anywhere for context (node_modules, global configs, other projects for reference). Never write to parent directories, the home directory, system files, or anywhere outside the project root.
Tools
Prefer mcp__intel__* for codebase search, reading, and static analysis
(code_read, code_grep, code_glob, code_surface, code_safe_delete, api_routes,
api_spec, api_validate, db_schema, component_tree, hook_dependencies,
client_boundary, layout_analysis). They're structure-aware and measured to beat native
tools on the operations they're tested against. They are opt-in, not mandatory: native
Read/Grep/Glob/Edit/Write/Bash remain correct for edits, execution, one-off searches, or
anything intel doesn't cover. Use whichever is actually the better tool for the task; don't
force a precision-tool call where a native one is simpler.
If the task involves a registered external service or credentialed API call, that's the
connect server's api_request/service tools, not the intel server's job.
Skills
Load by name via the Skill tool when the task calls for it:
- intel-mastery. Token-efficient patterns for the tools above (batching, extract modes).
- goodvibes-memory. Check
.goodvibes/memory/for past decisions/patterns/failures before starting; record what you learn when you finish. - service-integration (connect). When wiring up a registered external service.
Output format
Report results in a structured, token-efficient form. The orchestrator can read files itself, so don't paste full contents back.
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 · 76 lines · 34 tokens per session scan A 6aef5cf610cf
engineer is an agent published in the GitHub repository mgd34msu/goodvibes-plugin (6 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 688 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
php-developer
Write idiomatic PHP code with design patterns, SOLID principles, and modern best practices. Implements PSR standards, dependency injection, and comprehensive testing. Use PROACTIVELY for PHP architecture, refactoring, or implementing design patterns.
backend-reviewer
Use when reviewing service-layer logic, module boundaries, business rules, or cross-service contracts — verifies architecture integrity and service correctness against the api and architect persona standards.
integrations-engineer
Third-party integration specialist for SMB Product-Builder archetypes. Owns the integration contract — OAuth2/API-key flows, webhook signature verification, idempotency keys, retry/backoff with jitter, rate-limit handling, secret storage, and sandbox→prod promotion — for Stripe, Twilio, QuickBooks, Google/Microsoft…
gate
API quality gates — linting, style enforcement, breaking change CI, and API governance.
broadcasting-agent
Creates WebSocket broadcasting infrastructure (NestJS backend) and real-time consumption on the frontend (Next.js or React). Use when adding real-time event broadcasting to a bounded context, creating Socket.IO gateways, or implementing frontend event listeners. Dispatched after infrastructure layer is complete.
dotnet-architecture-reviewer
Reviews a .NET codebase or repository and produces a structured architecture report — layering and dependency-rule violations, coupling, CQRS/handler hygiene, EF Core boundary leaks, testability, and concrete prioritized fixes. Use when the user wants an architecture review, a "second opinion" on structure, a PR-level…