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 DataCovey/nornweave --skill nornweave-apigit clone --depth 1 https://github.com/DataCovey/nornweaveWrote 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/datacovey/nornweave/nornweave-api)<a href="https://agentmods.dev/skills/datacovey/nornweave/nornweave-api"><img src="https://agentmods.dev/badge/skills/datacovey/nornweave/nornweave-api/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/datacovey/nornweave/nornweave-api"><img src="https://agentmods.dev/badge/skills/datacovey/nornweave/nornweave-api.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 | $0.00077 | $0.02024 |
| Opus 5 | $0.00039 | $0.01012 |
| Sonnet 5 | $0.00015 | $0.00405 |
| Haiku 4.5 | $0.00008 | $0.00202 |
Grade A, and why
nornweave-api 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 10d 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NornWeave API
NornWeave is a self-hosted, open-source Inbox-as-a-Service API for AI agents. It provides a stateful email layer (Inboxes, Threads, History) and an intelligent layer (Markdown parsing, Semantic Search) optimized for LLMs.
Installation
# Python client
pip install nornweave-client
Setup
from nornweave_client import NornWeave
# Sync client
client = NornWeave(base_url="http://localhost:8000")
# Or async client
from nornweave_client import AsyncNornWeave
client = AsyncNornWeave(base_url="http://localhost:8000")
Inboxes
Create scalable inboxes on-demand. Each inbox has a unique email address based on your configured domain.
# Create inbox with username and display name
inbox = client.inboxes.create(
name="Support",
email_username="support"
)
# Result: [email protected]
# List all inboxes (paginated)
for inbox in client.inboxes.list():
print(inbox.email_address)
# Get inbox by ID
inbox = client.inboxes.get(inbox_id="inbox-uuid")
# Delete inbox
client.inboxes.delete(inbox_id="inbox-uuid")
Async Usage
# Create inbox
inbox = await client.inboxes.create(
name="Support",
email_username="support"
)
# List inboxes with async iteration
async for inbox in client.inboxes.list():
print(inbox.email_address)
# Get and delete
inbox = await client.inboxes.get(inbox_id="inbox-uuid")
await client.inboxes.delete(inbox_id="inbox-uuid")
Messages
Send and retrieve messages. NornWeave automatically converts content to Markdown for LLM consumption.
# Send message (body is Markdown)
response = client.messages.send(
inbox_id="inbox-uuid",
to=["[email protected]"],
subject="Hello from my AI agent",
body="# Welcome\n\nThis is a **markdown** email."
)
print(f"Message ID: {response.id}, Status: {response.status}")
# Reply to existing thread
response = client.messages.send(
inbox_id="inbox-uuid",
to=["[email protected]"],
subject="Re: Hello",
body="Thanks for your message!",
reply_to_thread_id="thread-uuid"
)
# List messages for an inbox (paginated)
for message in client.messages.list(inbox_id="inbox-uuid"):
print(f"[{message.direction}] {message.content_clean[:100]}")
# Get single message by ID
message = client.messages.get(message_id="message-uuid")
print(message.content_clean) # LLM-ready markdown content
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 314 lines · 77 tokens per session scan A 18cd4ff238b7
nornweave-api is a skill published in the GitHub repository DataCovey/nornweave (27 stars, last pushed 9d ago), licensed Apache-2.0. It adds 77 tokens to every session and 2,024 once invoked, about $0.0004 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.
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