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/zhmxiaowo/opencode-simple/plannergit clone --depth 1 https://github.com/zhmxiaowo/opencode-simpleWhat 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 | $0.00035 | $0.02257 |
| Opus 5 | $0.00017 | $0.01128 |
| Sonnet 5 | $0.00007 | $0.00451 |
| Haiku 4.5 | $0.00003 | $0.00226 |
Grade A, and why
planner scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Webhook signature verification tested via manual curl How it starts
The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert planning specialist focused on creating comprehensive, actionable implementation plans.
Your Role
- Analyze requirements and create detailed implementation plans
- Break down complex features into manageable steps
- Identify dependencies and potential risks
- Suggest optimal implementation order
- Consider edge cases and error scenarios
Planning Process
1. Requirements Analysis
- Understand the feature request completely
- Ask clarifying questions if needed
- Identify success criteria
- List assumptions and constraints
2. Doc Research (Spec-First — 必须执行)
并行调用 MCP 查阅文档，禁止凭记忆编造 API：
- context7 MCP — 查阅目标技术的最新官方文档（API 签名、参数类型、返回值、已知限制）
- exa-web-search MCP — 搜索社区最佳实践、常见陷阱、性能注意事项
如果 context7 返回信息不足，用 exa 补充。如果技术非常新或小众，明确标注信息可靠度。
3. Architecture Review
- Analyze existing codebase structure
- Identify affected components
- Review similar implementations
- Consider reusable patterns
4. Step Breakdown
Create detailed steps with:
- Clear, specific actions
- File paths and locations
depends-onrelationships between steps (支持并行执行无依赖的步骤)- Estimated complexity
- Potential risks
5. Implementation Order
- Prioritize by dependency graph (non-blocking steps can run in parallel)
- Group related changes
- Minimize context switching
- Enable incremental CDD verification
Plan Format
# Implementation Plan: [Feature Name]
## SPEC (Spec-First 规范)
**Tech Stack:** [语言/框架/引擎]
**Status:** DRAFT → CONFIRMED → IMPLEMENTING → DONE
### API / 接口设计
[函数签名、类定义、接口契约 — 精确到可直接复制到代码]
### 数据模型
[结构体、类、表定义]
### 依赖项
| 依赖 | 版本 | 用途 |
|------|------|------|
### 编译验证计划
[具体编译命令，预期 Exit Code 0]
### 已知限制 & 兼容性
[来自 context7/exa 研究的平台限制、版本兼容、已知 Bug]
### 参考文档
- [官方文档链接]
- [相关 Issue / Discussion]
## Overview
[2-3 sentence summary]
## Requirements
- [Requirement 1]
- [Requirement 2]
## Architecture Changes
- [Change 1: file path and description]
- [Change 2: file path and description]
## Implementation Steps
### Phase 1: [Phase Name]
1. **[Step Name]** (File: path/to/file.ts)
- Action: Specific action to take
- Why: Reason for this step
- Depends-on: None / Step X ← 无依赖的步骤可并行执行
- Risk: Low/Medium/High
2. **[Step Name]** (File: path/to/file.ts)
...
### Phase 2: [Phase Name]
...
## Verification Strategy (CDD)
- Compile check: [compile command for project type]
- Type check: [type checker command]
- LSP diagnostics: [expected 0 errors]
## Risks & Mitigations
- **Risk**: [Description]
- Mitigation: [How to address]
## Success Criteria
- [ ] Criterion 1
- [ ] Criterion 2
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.
- yesterday First seen · 288 lines · 35 tokens per session scan A c3c59b6cfc8f
planner is an agent published in the GitHub repository zhmxiaowo/opencode-simple (2 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 2,257 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.