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 monte-carlo-data/mc-agent-toolkit --skill connection-auth-rulesgit clone --depth 1 https://github.com/monte-carlo-data/mc-agent-toolkitWrote 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/monte-carlo-data/mc-agent-toolkit/connection-auth-rules)<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/connection-auth-rules"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/connection-auth-rules/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/monte-carlo-data/mc-agent-toolkit/connection-auth-rules"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/connection-auth-rules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 20 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00032 | $0.01752 |
| Opus 5.5 | $0.00013 | $0.00701 |
| Sonnet 5.5 | $0.00006 | $0.00350 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
connection-auth-rules 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 1mo 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connection Auth Rules Builder
Use this skill when the user wants to build a Connection Auth Rules (stored as ctp_config) for a Monte Carlo connection. The config is stored on the Connection object in the monolith and tells the Apollo agent how to transform flat credentials into the driver-specific connect_args format.
When to activate this skill
Activate when the user:
- Asks to create, build, or generate a Connection Auth Rules
- Asks what fields are needed for a connection type's Connection Auth Rules
- Wants to customize credential transformation for a connection
- Asks about
MapperConfig,TransformStep, orCtpConfig - Says things like "help me write Connection Auth Rules for X", "what's the connection auth rules format for X"
When NOT to activate this skill
Do not activate when the user is:
- Creating monitors (use the monitor-creation skill)
- Investigating data incidents (use the analyze-root-cause skill)
- Setting up a connection in the UI (this skill builds the JSON config, not UI flows)
Step 1 — List available connection types
Locate the companion script with Bash:
find -L ~/.claude . -name fetch_schema.py -path "*/connection-auth-rules/*" 2>/dev/null | head -1
Then run it:
python3 <script_path> --list
The script outputs JSON. Parse result.connectors — each entry has a name field. Present the names to the user and ask which connection type they want to build a config for.
If the script fails: Show the error output and offer to retry. Do not proceed until you have the connector list.
Step 2 — Fetch the connector schema
Once the user selects a connection type, run the script with that connector name:
python3 <script_path> --connector <name>
The script outputs JSON. Parse result.schema:
output_keys— the driver-levelconnect_argskeys the mapper must produce (from the connector'sTypedDict)default_field_map— the existing default mapping (credential field → Jinja2 template)default_steps— any default transform steps already configured
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.
- 1mo ago First seen · 178 lines · 32 tokens per session scan A a11125c52686
connection-auth-rules is a skill published in the GitHub repository monte-carlo-data/mc-agent-toolkit (93 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 1,752 once invoked, about $0.0001 per session on Opus 5.5. 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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