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 commands/przeprogramowani/10x-bench/10x-plangit clone --depth 1 https://github.com/przeprogramowani/10x-benchWrote 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/commands/przeprogramowani/10x-bench/10x-plan)<a href="https://agentmods.dev/commands/przeprogramowani/10x-bench/10x-plan"><img src="https://agentmods.dev/badge/commands/przeprogramowani/10x-bench/10x-plan.svg" alt="Measured on agentmods" 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 | $0.00009 | $0.05954 |
| Opus 5 | $0.00005 | $0.02977 |
| Sonnet 5 | $0.00002 | $0.01191 |
| Haiku 4.5 | $0.00001 | $0.00595 |
Grade A, and why
10x-plan 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- [ ] API endpoint returns 200: `curl localhost:8080/api/new-endpoint` How it starts
The opening of the file, as written. The whole thing — 682 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Plan
You are tasked with creating detailed implementation plans through an interactive, iterative process. You should be skeptical, thorough, and work collaboratively with the user to produce high-quality technical specifications.
Initial Response
When this command is invoked:
-
Check if parameters were provided:
- If a file path or ticket reference was provided as a parameter, skip the default message
- Immediately read any provided files FULLY
- Begin the research process
-
If no parameters provided, respond with:
I'll help you create a detailed implementation plan. Let me start by understanding what we're building.
Please provide:
1. The task/ticket description (or reference to a ticket file)
2. Any relevant context, constraints, or specific requirements
3. Links to related research or previous implementations
I'll analyze this information and work with you to create a comprehensive plan.
Tip: You can also invoke this command with a ticket file directly: `/create_plan thoughts/allison/tickets/eng_1234.md`
For deeper analysis, try: `/create_plan think deeply about thoughts/allison/tickets/eng_1234.md`
Then wait for the user's input.
Process Steps
Step 1: Context Gathering & Initial Analysis
-
Read all mentioned files immediately and FULLY:
- Ticket files (e.g.,
thoughts/allison/tickets/eng_1234.md) - Research documents
- Related implementation plans
- Any JSON/data files mentioned
- IMPORTANT: Use the Read tool WITHOUT limit/offset parameters to read entire files
- CRITICAL: DO NOT spawn sub-tasks before reading these files yourself in the main context
- NEVER read files partially - if a file is mentioned, read it completely
- Ticket files (e.g.,
-
Spawn initial research tasks to gather context: Before asking the user any questions, use specialized agents to research in parallel:
- Use the codebase-locator agent to find all files related to the ticket/task
- Use the codebase-analyzer agent to understand how the current implementation works
- If relevant, use the thoughts-locator agent to find any existing thoughts documents about this feature
- If a Linear ticket is mentioned, use the linear-ticket-reader agent to get full details
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.
- 3d ago First seen · 682 lines · 9 tokens per session scan A 83041a25daba
10x-plan is a command published in the GitHub repository przeprogramowani/10x-bench (11 stars, last pushed 16d ago), licensed MIT. It adds 9 tokens to every session and 5,954 once invoked, about $0.0000 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 2026-08-30.
Other commands, from other repositories
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build
Run full verification pipeline.
release
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add-agent
引导新增一个 Agent 适配器。用法 /add-agent.
migrate
Command "migrate" from chohra-med/expo_boilerplate, covering invocation, steps and rule.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.