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 instructions/scanaislop/aislop/gemini-mdgit clone --depth 1 https://github.com/scanaislop/aislopWrote 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/instructions/scanaislop/aislop/gemini-md)<a href="https://agentmods.dev/instructions/scanaislop/aislop/gemini-md"><img src="https://agentmods.dev/badge/instructions/scanaislop/aislop/gemini-md.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 | $0.00005 | $0.00005 |
| Opus 5 | $0.00003 | $0.00003 |
| Sonnet 5 | $0.00001 | $0.00001 |
| Haiku 4.5 | $0.00001 | $0.00001 |
Grade A, and why
aislop GEMINI.md 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 5d 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.
This is a copy
100% identical to deepseek-harness CLAUDE.md — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
@AGENTS.md
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.
- 5d ago First seen · 2 lines · 5 tokens per session scan A 336cc4fbf19b
aislop GEMINI.md is an instructions file published in the GitHub repository scanaislop/aislop (593 stars, last pushed 4d ago), licensed MIT. It adds 5 tokens to every session, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to deepseek-harness CLAUDE.md, differing in 3 lines, and is treated as a copy.
Other instructions, from other repositories
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Instructions for AsyrafHussin/agent-skills, covering agent skills repository, skills overview, usage and contributing.
drift drift-rag-grounding.instructions.md
Nutze diese Instruction, wenn ein Coding-Agent Behauptungen ueber drifts eigene Policy, Signale, ADR-Entscheidungen, Audit-Ergebnisse oder Benchmark-Evidence aufstellt. Sie verpflichtet zur Zitation verifizierter Fact-IDs via driftretrieve und driftcite (ADR-091).
drift drift-prompt-engineering.instructions.md
Nutze diese Instruction, wenn Prompts, Instructions, Skills, Agents oder Copilot-Customization in Drift erstellt, geschärft oder reviewt werden. Fokus: discovery-taugliches Frontmatter, enge applyTo-Scopes, Shared-Partials-Wiederverwendung, Artefaktvertraege und Anti-Halluzinationsregeln fuer Prompt-Engineering.
agent-skills CLAUDE.md
Instructions for AsyrafHussin/agent-skills, a project described as: Skills for AI coding agents — Laravel, PHP, React, TypeScript, testing, security, and code quality.
GPT-RAG release.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.
apex-accelerator vendor-prompting.instructions.md
Vendor prompting best-practice rules for Anthropic Claude and OpenAI GPT-5.6-Terra agents and prompts. Each rule cites a rule ID in the vendor-prompting skill rules.json registry. Validator: npm run lint:vendor-prompting.