csv-over-json-tables

csv-over-json-tables is a skill for Claude Code from alivirgo/Major-AI-Skills. It costs 23 tokens per session (1,119 once invoked), scanned A, original, MIT.

A format for sending table-shaped data as CSV or TSV instead of an array of JSON objects. CSV means comma-separated values, and TSV uses tabs; both define column names once at the top.

In plain words
What is it for?
Use it for customer records, database results, transactions, server metrics, and other datasets organized into rows and columns.
Why use it?
It avoids repeating the same column names and JSON punctuation on every row, making large tables more compact for transmission and analysis.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument; mentions Codex.

Part of the mas-efficiency-pack plugin — 5 skills shipped together

Good fit Use it for customer records, database results, transactions, server metrics, and other datasets organized into rows and columns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alivirgo/major-ai-skills/csv-over-json-tables
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 alivirgo/Major-AI-Skills --skill csv-over-json-tables
Clone the repo
git clone --depth 1 https://github.com/alivirgo/Major-AI-Skills

Made for: Claude Code.

Or install mas-efficiency-pack, the plugin that ships this one along with the rest of its 5 skills.

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.

agentmods badge for csv-over-json-tables

README.md
[![agentmods](https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/csv-over-json-tables/github.svg)](https://agentmods.dev/skills/alivirgo/major-ai-skills/csv-over-json-tables)
Your own site
<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/csv-over-json-tables"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/csv-over-json-tables/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.

agentmods 80×15 button for csv-over-json-tables

Your own site · 80×15
<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/csv-over-json-tables"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/csv-over-json-tables.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,119 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.01119
Opus 5 $0.00012 $0.00560
Sonnet 5 $0.00005 $0.00224
Haiku 4.5 $0.00002 $0.00112

Measured today against content hash 82af25c0085f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

csv-over-json-tables 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 today.

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.

plugins/mas-efficiency-pack/skills/csv-over-json-tables/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tabular Serialization Protocol (CSV / TSV over JSON Arrays)

Overview

When an LLM extracts or analyzes tabular datasets (e.g., customer transaction lists, database query results, or server metric logs), defaulting to an array of JSON objects forces the model to repeat every column key on every single row ("first_name": "...", "transaction_amount": "...", "status": "...").

In a 100-row dataset, repeating JSON keys burns thousands of redundant tokens purely on structural quotation marks, colons, and braces.

The Tabular Serialization Protocol replaces JSON object arrays with Comma-Separated Values (CSV) or Tab-Separated Values (TSV) - defining the header keys once at row 1 and streaming raw comma-delimited data rows, cutting token usage by 65% to 75%.


JSON Object Array vs. CSV Data Stream

┌─────────────────────────────────────────────────────────────┐
│                 Tabular Payload Comparison                  │
│                                                             │
│  JSON Object Array (145 Tokens for 2 Rows):                 │
│  [                                                          │
│    {"user_id": 101, "email": "[email protected]", "tier": "pro"}│
│    {"user_id": 102, "email": "[email protected]", "tier": "free"} │
│  ]                                                          │
│  ↳ Keys `user_id`, `email`, `tier` repeated on every row!   │
│                                                             │
│  CSV Data Stream (34 Tokens - 76.5% Reduction!):            │
│  user_id,email,tier                                         │
│  101,[email protected],pro                                      │
│  102,[email protected],free                                       │
│  ↳ Keys defined ONCE. Zero quotation/brace syntax waste.    │
└─────────────────────────────────────────────────────────────┘

The Master CSV Extraction Prompt Template

When querying an LLM to extract or output structured rows:

Extract the customer records from the text below:
<source_data>
[PASTE UNSTRUCTURED TEXT]
</source_data>

Output Constraints:
- Format as raw **CSV (Comma-Separated Values)**.
- Line 1 MUST be the exact header row: `user_id,name,email,plan_tier,monthly_spend`
- Do NOT output JSON.
- Output ONLY the CSV block; zero introductory or concluding commentary.

Read the full file on GitHub · 115 lines

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.

  1. today Changed · -13 tokens per session 82af25c0085f
  2. 12d ago First seen · 115 lines · 36 tokens per session scan A 37a54e80b121

Subscribe to this mod's changes

csv-over-json-tables is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 1,119 once invoked, about $0.0001 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 2026-08-31.

Related

Other skills, from other repositories

snip

You are an expert at writing declarative YAML filters for snip, a CLI proxy that reduces LLM token consumption by filtering shell output.

edouard-claude/snip · 0 tokens

azure-pipelines

Expert knowledge for Azure Pipelines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing agents/secrets, configuring YAML builds, migrating from Jenkins…

MicrosoftDocs/Agent-Skills · 116 tokens

azure-local

Expert knowledge for Azure Local development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning Azure Local racks/SDN, disconnected clusters, Arc VMs, GPU workloads, or…

MicrosoftDocs/Agent-Skills · 112 tokens

azure-arc

Expert knowledge for Azure Arc development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing Arc-enabled Kubernetes, data services, Edge Volumes, Agentic Retrieval APIs…

MicrosoftDocs/Agent-Skills · 114 tokens

azure-blob-storage

Expert knowledge for Azure Blob Storage development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Blob tiers, lifecycle/immutability, NFS/SFTP mounts, static sites, or SDK/CLI data workflows, and…

MicrosoftDocs/Agent-Skills · 112 tokens

azure-defender-for-cloud

Expert knowledge for Azure Defender For Cloud development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing VMs, containers/AKS, SQL, storage, multi‑cloud connectors, or…

MicrosoftDocs/Agent-Skills · 127 tokens