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CF data-engineering

Design and operate data infrastructure — database operations (vector, relational, graph, time-series), ETL/ELT pipeline design (dbt patterns, incremental loading), SQL analytical patterns, data quality monitoring, schema migration, and storage infrastructure management, including model-assisted transformation contracts, deterministic acceptance, bounded retries, and sink reconciliation. Do not use for statistical analysis or ML model development.

magnus919/agent-skills Agent Skills author: magnus919 MIT 14 files body ≈ 1 312 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Design and operate data infrastructure — database operations (vector, relational, graph, time-series), ETL/ELT pipeline design (dbt patterns, incremental…

As a process F 39/100 · Will not run — References files that are not bundled: ../postgres/SKILL.md, ../supabase/SKILL.md, ../supabase/references/agent-evals.md

AnalyzerSupabasePostgreSQLInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: ../postgres/SKILL.md, ../supabase/SKILL.md, ../supabase/references/agent-evals.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-pipe-to-shell references/graph-databases.md:1143
    Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
    curl -sSfL https://neo4j.sh/install.sh | bash
    security skill

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../postgres/SKILL.md
  • warning missing-ref reference to a missing file: ../supabase/SKILL.md
  • warning missing-ref reference to a missing file: ../supabase/references/agent-evals.md

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: ../postgres/SKILL.md, ../supabase/SKILL.md, ../supabase/references/agent-evals.md
  • 0Tools and files. 3 referenced file(s) missing: ../postgres/SKILL.md, ../supabase/SKILL.md, ../supabase/references/agent-evals.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50Steps. 2 steps
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1312 tokens
  • low No test case covers injection arriving through data

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 450: enough signal without eating the budget
  • +4Structure: 5 headings
  • +4Reference files are cited in the instructions (10 of 10)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.