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/jmanhype/claude-code-plugin-marketplace/agents-mdgit clone --depth 1 https://github.com/jmanhype/claude-code-plugin-marketplaceWrote 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/jmanhype/claude-code-plugin-marketplace/agents-md)<a href="https://agentmods.dev/instructions/jmanhype/claude-code-plugin-marketplace/agents-md"><img src="https://agentmods.dev/badge/instructions/jmanhype/claude-code-plugin-marketplace/agents-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 | $0.00572 | $0.00572 |
| Opus 5 | $0.00286 | $0.00286 |
| Sonnet 5 | $0.00114 | $0.00114 |
| Haiku 4.5 | $0.00057 | $0.00057 |
Grade A, and why
claude-code-plugin-marketplace AGENTS.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.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Project Structure & Module Organization
qts/contains the Quantitative Trading System core modules (risk controls, execution, orchestration). Keep new pipeline logic colocated with adjacent modules (e.g., order routing inexecutor.py).plugins/hosts marketplace-ready agent plugins; each subdirectory ships aplugin.jsonmanifest and optional README describing intended use.config/stores default runtime JSON (risk configs, provider presets);schemas/holds JSON Schema definitions used by validators.scripts/includes operational utilities such asvalidate_marketplace.py;examples/anddata/provide sample sessions and fixtures for demos;logs/retains ACE/QTS run artifacts for troubleshooting.
Build, Test, and Development Commands
- Create an isolated environment before modifying agents:
python -m venv .venv && source .venv/bin/activate pip install -r requirements.txt - Run simulated trading sessions locally:
PYTHONPATH=. python -m qts.main --symbols ETH SOL XRP --llm-provider mock - Validate marketplace metadata before publishing:
python scripts/validate_marketplace.py
Coding Style & Naming Conventions
- Python modules use 4-space indentation, type hints, and descriptive docstrings focused on risk assumptions and agent hand-offs.
- Keep filenames and identifiers snake_case; reserve PascalCase for classes and ALL_CAPS for immutable configuration keys.
- Format with
black .and lint withflake8 qts pluginswhen available; update manifests with minimal JSON diff and sorted keys.
Testing Guidelines
- Prefer
pytestfor unit and integration coverage; mirror source tree structure undertests/(e.g.,tests/test_risk.pyforqts/risk.py). - Record deterministic mocks in
data/fixtures/and assert against ACE bullet outputs stored underlogs/. - Target critical risk and execution paths first; gate new trading modes on simulated drawdown tests before requesting review.
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 · 42 lines · 572 tokens per session scan A 52efa23b8153
claude-code-plugin-marketplace AGENTS.md is an instructions file published in the GitHub repository jmanhype/claude-code-plugin-marketplace (27 stars, last pushed yesterday), licensed MIT. It adds 572 tokens to every session, about $0.0029 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.