Borrowing it
Nothing to install: this file belongs to macromania/agentop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/macromania/agentop/main/.github/skills/agentop-conventions/SKILL.mdgit clone --depth 1 https://github.com/macromania/agentopWrote 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/macromania/agentop/agentop-conventions)<a href="https://agentmods.dev/skills/macromania/agentop/agentop-conventions"><img src="https://agentmods.dev/badge/skills/macromania/agentop/agentop-conventions/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/macromania/agentop/agentop-conventions"><img src="https://agentmods.dev/badge/skills/macromania/agentop/agentop-conventions.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 | $0.00077 | $0.03252 |
| Opus 5.5 | $0.00031 | $0.01301 |
| Sonnet 5.5 | $0.00015 | $0.00650 |
| Haiku 4.5 | $0.00008 | $0.00325 |
Grade A, and why
agentop-conventions 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 2mo 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 — 530 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentOp Project Conventions
Core domain model, attention system, and architectural patterns specific to AgentOp.
When to Use This Skill
- Implementing features touching the core domain
- Working with task hierarchies
- Handling agent sessions and steps
- Implementing the attention system
- Building decision point flows
- Adding new entity types
Core Data Model
Entity Relationships
Task (tree hierarchy via parentId)
└── Outcome (many per task, represents expected results)
└── AgentSession (many per outcome, AI execution attempts)
└── AgentStep (stream of: thinking | action | decision_point)
└── DecisionPoint (user approval for sensitive actions)
Type Definitions
// packages/core/src/types.ts
// ============================================
// Enums
// ============================================
export type TaskStatus =
| 'pending' // Not started
| 'in_progress' // Being worked on
| 'completed' // Successfully done
| 'blocked'; // Waiting on dependency
export type AttentionType =
| 'supervised' // Every action needs approval
| 'delegated' // Runs autonomously
| 'sensitive'; // Only sensitive actions need approval
export type SessionStatus =
| 'pending' // Queued to start
| 'running' // Currently executing
| 'completed' // Finished successfully
| 'error' // Failed with error
| 'cancelled'; // User cancelled
export type StepType =
| 'thinking' // LLM reasoning output
| 'action' // Tool execution
| 'decision_point'; // Awaiting user decision
export type DecisionStatus =
| 'pending' // Waiting for user
| 'approved' // User approved
| 'denied' // User denied
| 'timeout'; // Auto-denied after timeout
// ============================================
// Entities
// ============================================
export interface Task {
id: string;
title: string;
description?: string;
parentId: string | null; // null = root task
status: TaskStatus;
attentionType: AttentionType;
orderIndex: number; // Fractional index for drag reorder
createdAt: Date;
updatedAt: Date;
}
export interface Outcome {
id: string;
taskId: string;
title: string;
description?: string;
status: TaskStatus;
createdAt: Date;
updatedAt: Date;
}
export interface AgentSession {
id: string;
outcomeId: string;
status: SessionStatus;
attentionType: AttentionType;
startedAt: Date;
completedAt?: Date;
error?: string;
tokenUsage?: {
prompt: number;
completion: number;
total: number;
};
}
export interface AgentStep {
id: string;
sessionId: string;
type: StepType;
status: 'in_progress' | 'completed' | 'error' | DecisionStatus;
content?: string; // For thinking steps
toolCall?: ToolCall; // For action steps
result?: ToolResult; // After tool execution
createdAt: Date;
}
export interface ToolCall {
id: string;
name: string;
arguments: Record<string, unknown>;
}
export interface ToolResult {
success: boolean;
result?: string;
error?: string;
}
// ============================================
// Event Log (Immutable Audit Trail)
// ============================================
export interface EventLog {
id: string;
timestamp: Date;
eventType: string;
entityType: 'task' | 'outcome' | 'session' | 'step';
entityId: string;
payload: Record<string, unknown>;
userId?: string;
}
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.
- 2mo ago First seen · 530 lines · 77 tokens per session scan A 4d3b04154faa
agentop-conventions is a skill published in the GitHub repository macromania/agentop (11 stars, last pushed 7mo ago), licensed MIT. It adds 77 tokens to every session and 3,252 once invoked, about $0.0003 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.
agentop-conventions compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| agentop-conventionsmacromania/agentop | Skill | 11 | 7mo ago | MIT | A | 77 | Claude Code, Codex |
| eval-dataset-designbojieli/ai-agent-book | Skill | 57k | 29d ago | Apache-2.0 | A | 138 | Claude Code, Codex |
| aatmf-t10-confidentiality-breachPurpleAILAB/Decepticon | Skill | 6.5k | 8d ago | Apache-2.0 | A | 39 | Claude Code, Codex |
| mochi-remindkirodotdev/KiroCrew | Skill | 4.8k | yesterday | Apache-2.0 | A | 20 | Claude Code, Codex |
| ensembl-databasesynthetic-sciences/openscience | Skill | 4.3k | 2d ago | Apache-2.0 | A | 45 | Claude Code, Codex |
| ai-musicZJU-REAL/Easel | Skill | 4.5k | 4d ago | Apache-2.0 | A | 161 | Claude Code, Codex |
| skill-news-intelligenceZJU-REAL/Easel | Skill | 4.5k | 4d ago | Apache-2.0 | A | 104 | Claude Code, Codex |