Macro is a shared workspace that brings email, chat, documents, tasks, AI agents, calls, and customer relationship management into one connected system. It is for teams that want work information and cross-references in a single searchable environment. The catalogue entries provide skills, instructions, MCP integrations, commands, settings, and an agent for working with Macro.
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 skills add macro-inc/macro --skill write_attachment_servicegit clone --depth 1 https://github.com/macro-inc/macroWrote 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/macro-inc/macro/write_attachment_service)<a href="https://agentmods.dev/skills/macro-inc/macro/write_attachment_service"><img src="https://agentmods.dev/badge/skills/macro-inc/macro/write_attachment_service/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/macro-inc/macro/write_attachment_service"><img src="https://agentmods.dev/badge/skills/macro-inc/macro/write_attachment_service.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.01573 |
| Opus 5.5 | $0.00000 | $0.00629 |
| Sonnet 5.5 | $0.00000 | $0.00315 |
| Haiku 4.5 | $0.00000 | $0.00157 |
Grade A, and why
WRITE_ATTACHMENT_SERVICE 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 151 lines · 0 tokens per session scan A 7cce0f39a368
WRITE_ATTACHMENT_SERVICE is a skill published in the GitHub repository macro-inc/macro (5,438 stars, last pushed today), licensed AGPL-3.0. It costs nothing until one of its globs matches a file; then it loads 1,573 tokens. 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 skills, from other repositories
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s-gw
Use s-gw when working with credentials, private keys, API tokens, SSH identities, browser credentials, or other sensitive data in agentic coding workflows. Prefer typed handles and local approved execution over exposing raw secret values to a model.
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open-source
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browseruse, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle…
deepstream-sop
Use this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the…