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 beel-collab/presets.dev --skill monte-carlo-push-ingestiongit clone --depth 1 https://github.com/beel-collab/presets.devWrote 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/beel-collab/presets.dev/monte-carlo-push-ingestion)<a href="https://agentmods.dev/skills/beel-collab/presets.dev/monte-carlo-push-ingestion"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/monte-carlo-push-ingestion/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/beel-collab/presets.dev/monte-carlo-push-ingestion"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/monte-carlo-push-ingestion.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00019 | $0.04271 |
| Opus 5 | $0.00010 | $0.02135 |
| Sonnet 5 | $0.00004 | $0.00854 |
| Haiku 4.5 | $0.00002 | $0.00427 |
Grade A, and why
monte-carlo-push-ingestion scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| `references/direct-http-api.md` | Customer wants to call push APIs directly via curl/HTTP without pycarlo | This is a copy
95% identical to push-ingestion — 28 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.
How it starts
The opening of the file, as written. The whole thing — 368 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monte Carlo Push Ingestion
You are an agent that helps customers collect metadata, lineage, and query logs from their data warehouses and push that data to Monte Carlo via the push ingestion API. The push model works with any data source — if the customer's warehouse does not have a ready-made template, derive the appropriate collection queries from that warehouse's system catalog or metadata APIs. The push format and pycarlo SDK calls are the same regardless of source.
Monte Carlo's push model lets customers send metadata, lineage, and query logs directly to Monte Carlo instead of waiting for the pull collector to gather it. It fills gaps the pull model cannot always cover — integrations that don't expose query history, custom lineage between non-warehouse assets, or customers who already have this data and want to send it directly.
When to Use
Use this skill when the user needs to collect metadata, lineage, freshness, volume, or query-log data from a warehouse or adjacent system and push it into Monte Carlo through the push-ingestion API.
Push data travels through the integration gateway → dedicated Kinesis streams → thin adapter/normalizer code → the same downstream systems that power the pull model. The only new infrastructure is the ingress layer; everything after it is shared.
MANDATORY — Always start from templates
When generating any push-ingestion script, you MUST:
- Read the corresponding template before writing any code. Templates live in this skill's
directory under
scripts/templates/<warehouse>/. To find them, glob for**/push-ingestion/scripts/templates/<warehouse>/*.py— this works regardless of where the skill is installed. Do NOT search from the current working directory alone. - Adapt the template to the customer's needs — do not write pycarlo imports, model constructors, or SDK method calls from memory.
- If no template exists for the target warehouse, read the Snowflake template as the canonical reference and adapt only the warehouse-specific collection queries.
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.
- 6d ago First seen · 368 lines · 19 tokens per session scan A f3124a177d46
monte-carlo-push-ingestion is a skill published in the GitHub repository beel-collab/presets.dev (3 stars, last pushed 4mo ago), licensed MIT. It adds 19 tokens to every session and 4,271 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to push-ingestion, differing in 28 lines, and is treated as a copy.
Other skills, from other repositories
bf-to-agents-sdk-typescript-migration
Assess and migrate JavaScript or TypeScript bots from BotBuilder/Bot Framework SDK to Microsoft 365 Agents SDK with AgentApplication. Use to produce a migration report and plan before editing code, map BotBuilder packages and APIs, identify unsupported features, and implement only the supported plan items selected by…
skill-creator-primer
You MUST load this skill before the skill-creator skill AND before making ANY change to, or conducting a review of ANY Agent Skill. Triggers include creating, editing, reviewing, or contributing to any part of an Agent Skill (description, frontmatter, body, references, scripts, trigger evals, conflicts, etc).
llm-wiki
Use when building or maintaining a self-contained personal knowledge base (an LLM wiki) in plain markdown. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki health, auditing article claims against their sources, critiquing a wiki source's reasoning, superseding stale knowledge, 'add to…
apply-mantel-styles
Provides guidelines for applying Mantel's brand styles to diagrams and frontend components. Use when asked to create visuals that need to align with Mantel's branding.
authoring-claude-md
Creating and maintaining CLAUDE.md project memory files and .claude/rules/ rule files that provide non-obvious codebase context. Use when (1) creating a new CLAUDE.md for a project, (2) adding architectural patterns or design decisions to existing CLAUDE.md, (3) capturing project-specific conventions that aren't…
swift-development
You MUST activate this skill when working on Swift projects.