A migration assessment workflow that examines converted database code and reports to build a migration plan. It can map dependencies, group objects into migration waves, identify dynamic SQL and anti-patterns, and summarize the workload.

It helps assess database code, organize objects into dependency-based waves, exclude selected objects, and prepare a multi-part Snowflake migration report.

Before migrating a large workload, teams need to know what depends on what, which objects are difficult, and what should be handled first. This workflow gathers those findings into an assessment.

assessment — Skill for Claude Code by sfc-gh-dflippo

Install

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.

Any agent

npx skills add sfc-gh-dflippo/snowflake-dbt-demo --skill assessment

Clone the repo

git clone --depth 1 https://github.com/sfc-gh-dflippo/snowflake-dbt-demo

Made for: Claude Code.

Or install snowflake-migration, the plugin that ships this one along with the rest of its 72 skills, 7 agents.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment/github.svg)](https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment)

Your own site

<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 13,265 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00075	$0.13265
Opus 5	$0.00037	$0.06633
Sonnet 5	$0.00015	$0.02653
Haiku 4.5	$0.00007	$0.01327

Measured 2d ago against content hash 8a8a8bf87e97, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

assessment 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 2d ago.

The scan reads SKILL.md. This mod also ships 31 executable files (etl-assessment/scripts/__init__.py, etl-assessment/scripts/dag_renderer/__init__.py, etl-assessment/scripts/dag_renderer/render_dags.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.claude/skills/snowflake-migration/skills/migration/assessment/SKILL.md · 1,083 lines

How it starts

The opening of the file, as written. The whole thing — 1,083 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assessment

On Entry

Tell the user:

Migration Assessment — I'll analyze your converted code to generate a migration plan: dependency waves, object categorization, dynamic SQL patterns, and a summary report. This helps us prioritize what to migrate first.

End-to-end migration assessment. The user only needs to point at the source — this skill detects the project state and, if needed, drives the migration setup (connect → init → register → convert) so that the SnowConvert reports the assessment depends on are produced automatically. The user is never asked for CSV paths, registry paths, or output directories.

One exception: SQL Server Discovery uses Extended Events (.xel) files, which the conversion pipeline does not produce. Step 4 first explains what Discovery adds, then lets the user skip it, provide .xel path(s) now, or take the capture SQL and provide the files on a later assessment run. The files stay in place; never copy them into the project.

"I want to assess my workload" → the user provides a source → assessment runs end-to-end. Nothing else is requested.

Step 0: Configure Session

Call the configure MCP tool with project_dir (use the current directory, or ask the user if ambiguous). Assessment needs no Snowflake connection — scai assessment runs entirely off the local project — so don't ask for one here; the setup machine asks after assessment, only if the user goes on to object migration. Other settings are filled in by sub-skills as the workflow progresses.

Step 1: Verify Prerequisites

If you arrived here directly (not through the setup state machine), call progress_setup() first. If it returns a next_task other than runAssessment (or completed: true with assessment already done), follow the engine — finish that setup step, then re-enter assessment when progress_setup() routes here.

Step 2: Auto-Detect SnowConvert Outputs

Resolve all inputs from project_dir. Do not prompt the user.

Input	Resolution
SCAI project root	`project_dir` (contains `.scai/` and the registry — required by `scai assessment waves`)
SnowConvert reports dir	`<project_dir>/reports/SnowConvert/`
Issues CSV	`<project_dir>/reports/SnowConvert/Issues.*.csv` (latest timestamp)
ETL Elements / Issues CSVs	`<project_dir>/reports/SnowConvert/ETL.Elements..csv` and `ETL.Issues..csv` (only if present — drives whether SSIS analysis is included)
Assessment output dir	`<project_dir>/assessment/` (created by `scai assessment waves`; fall back to creating if missing for other sub-skills)

Read the full file on GitHub · 1,083 lines

Files

What ships with it

60 files 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.

Changes

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 First seen · 1,083 lines · 75 tokens per session scan A 8a8a8bf87e97

Subscribe to this mod's changes

assessment is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 3d ago), licensed Apache-2.0. It adds 75 tokens to every session and 13,265 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 2026-09-10.

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