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 wardawgmalvicious/agent-config --skill fabric-sparkgit clone --depth 1 https://github.com/wardawgmalvicious/agent-configWrote 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/wardawgmalvicious/agent-config/fabric-spark)<a href="https://agentmods.dev/skills/wardawgmalvicious/agent-config/fabric-spark"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-spark/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/wardawgmalvicious/agent-config/fabric-spark"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/fabric-spark.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 | $0.00223 | $0.02800 |
| Opus 5 | $0.00112 | $0.01400 |
| Sonnet 5 | $0.00045 | $0.00560 |
| Haiku 4.5 | $0.00022 | $0.00280 |
Grade A, and why
fabric-spark 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 2d 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.
- Fabric Spark cannot access arbitrary external HTTP/HTTPS URLs — land data in lakehouse `Files/` first (via pipeline Copy activity, OneLake API, or curl) How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spark / PySpark in Fabric
Key Constraints
- Fabric Spark cannot access arbitrary external HTTP/HTTPS URLs — land data in lakehouse
Files/first (via pipeline Copy activity, OneLake API, or curl) - Use
abfss://URI format for OneLake paths in Spark:abfss://{workspace}@onelake.dfs.fabric.microsoft.com/{item}.Lakehouse/{path} - Use workspace GUIDs (not names) in ABFS URIs — spaces are not allowed
mssparkutilsfor Fabric-specific notebook operations (credentials, secrets, file management)- Use Delta Lake format for all Lakehouse tables
Runtime Context vs Spark Session Config
Two different things that are often confused:
| Need | API |
|---|---|
| Workspace / item identity (workspace ID + name, notebook ID + name, default lakehouse ID + name, userId) | notebookutils.runtime.context["currentWorkspaceId"] (etc.) — a dict, documented public API, works in pure-Python notebooks |
| Spark session tuning (shuffle partitions, AQE, Delta settings, case sensitivity) | spark.conf.set(...) / spark.conf.get(...) |
spark.conf.get("trident.workspace.id") also returns the workspace ID but is internal Spark conf, not documented surface, and is unavailable in pure-Python notebooks. Prefer notebookutils.runtime.context for identity lookups; reserve spark.conf.* for session tuning.
Lakehouse Setup
enableSchemasis set at lakehouse creation time only — cannot be retrofitted. Without it the lakehouse only has the defaultdboschema and you must recreate to gain named schemas. Set viacreationPayload: { "enableSchemas": true }onPOST /workspaces/{ws}/items(see fabric-rest-api skill).- Schemas use lowercase names by convention (
bronze/silver/goldfor medallion).DROP SCHEMA <name> CASCADEremoves the schema with all its tables. - Cross-lakehouse Spark SQL uses 3-part names:
lakehouse.schema.tablefor same-workspace,workspace.lakehouse.schema.tablefor cross-workspace. Verify access permissions on each lakehouse. - Lakehouse delete cascades irreversibly: SQL Endpoint deleted, all OneLake data permanently removed, shortcuts pointing in become inaccessible, dependent notebooks fail at runtime.
- Shortcuts as definition payload: when authoring a Lakehouse via REST,
shortcuts.metadata.jsonis an array of{name, path, target}objects. Supportedtarget.typevalues:OneLake,AdlsGen2,AmazonS3,GoogleCloudStorage,S3Compatible,Dataverse. Each target type has its own connection properties (see fabric-rest-api skill).
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.
- 2d ago Changed cfe9364b4c66
- 8d ago Changed · +3 lines 16b18666f309
- 12d ago First seen · 166 lines · 223 tokens per session scan A d277b959942c
fabric-spark is a skill published in the GitHub repository wardawgmalvicious/agent-config (1 stars, last pushed yesterday), licensed MIT. It adds 223 tokens to every session and 2,800 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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