oh-my-opencode-slim is a plugin that coordinates multiple specialized AI agents inside OpenCode, assigning codebase exploration, documentation research, architecture review, design, and implementation to different agents. It is for developers who want agent teams to divide and reconcile software-development work while mixing models from different providers. The catalogue entries are the plugin’s bundled agents, skills, and instruction.
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 skills add alvinunreal/oh-my-opencode-slim --skill verification-planninggit clone --depth 1 https://github.com/alvinunreal/oh-my-opencode-slimWrote 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/skills/alvinunreal/oh-my-opencode-slim/verification-planning)<a href="https://agentmods.dev/skills/alvinunreal/oh-my-opencode-slim/verification-planning"><img src="https://agentmods.dev/badge/skills/alvinunreal/oh-my-opencode-slim/verification-planning/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/skills/alvinunreal/oh-my-opencode-slim/verification-planning"><img src="https://agentmods.dev/badge/skills/alvinunreal/oh-my-opencode-slim/verification-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.00887 |
| Opus 5 | $0.00022 | $0.00443 |
| Sonnet 5 | $0.00009 | $0.00177 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
verification-planning 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- verification-planning — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verification Planning
Build an evidence path
Before changing a non-trivial system, build an evidence path: a project-specific route from the claim being made to evidence that can establish, limit, or refute it.
The purpose is not to select a familiar technique. The purpose is to decide how this system can reveal the truth of this particular change.
1. Frame the claim
State the behavior that needs to become true and the conditions that could make a confident conclusion wrong.
Consider what must change, what must remain true, where the behavior crosses a boundary, and which failure would matter most.
Complete when: the claim, its meaningful uncertainty, and its important failure modes are concrete enough to investigate.
2. Design the evidence path
Derive possible evidence paths from the system itself: its controllable inputs, observable effects, state transitions, invariants, boundaries, artifacts, and ability to repeat or reverse a scenario.
Generate alternatives before choosing. Prefer the path that produces a trustworthy conclusion with proportionate cost, safety, and effort.
Complete when: there is a preferred path, its limitations are understood, and a weaker or stronger alternative is available if circumstances change.
Set a verification budget
At the final state, state the distinct claims, assign one owner to establish or refute each, and choose the minimum non-duplicative evidence that covers the claims and important boundaries. Reuse evidence only while its relevant code, inputs, environment, and state remain valid. Required repository and release checks still apply; broaden or repeat verification only when a stated condition justifies it.
3. Create a verification affordance when needed
When the existing system leaves the decisive truth too indirect or ambiguous, extend the evidence path with a verification affordance: the smallest capability that makes the relevant state controllable, observable, repeatable, and diagnosable for an agent.
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.
- 10d ago First seen · 112 lines · 43 tokens per session scan A 7d2f4db38901
verification-planning is a skill published in the GitHub repository alvinunreal/oh-my-opencode-slim (8,740 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 887 once invoked, about $0.0002 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.
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java-patterns
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python-patterns
Python idioms — type hints, dataclasses, async/await, generators, pytest, common pitfalls. Activate when writing or reviewing Python code.
rust-patterns
Rust patterns covering ownership, lifetimes, error handling, traits, async with Tokio, and smart pointers. Activate when writing or reviewing Rust.