json-result-formatting

json-result-formatting is a skill for Claude Code, Codex from cxcscmu/SkillLearnBench. It costs 16 tokens per session (1,182 once invoked), scanned A, original, MIT.

A formatter for turning query results into structured JSON. Each question gets an answer list and a token-use count.

In plain words
What is it for?
Use it to build JSON result files, keep answers as lists, record token consumption, and prepare data for later processing.
Why use it?
It prevents inconsistent result shapes and makes output easier for other programs to read.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/cxcscmu/skilllearnbench/json-result-formatting
Any agent
npx skills add cxcscmu/SkillLearnBench --skill json-result-formatting
Clone the repo
git clone --depth 1 https://github.com/cxcscmu/SkillLearnBench

Made for: Claude Code, Codex.

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 json-result-formatting

README.md
[![agentmods](https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/json-result-formatting.svg)](https://agentmods.dev/skills/cxcscmu/skilllearnbench/json-result-formatting)
Your own site
<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/json-result-formatting"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/json-result-formatting.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,182 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00016 $0.01182
Opus 5 $0.00008 $0.00591
Sonnet 5 $0.00003 $0.00236
Haiku 4.5 $0.00002 $0.00118

Measured 4d ago against content hash c082bdf6d4aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

json-result-formatting 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 4d 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.

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.

skills/b1-one-shot-claude-haiku-4-5/enterprise-information-search/json-result-formatting/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

JSON Result Formatting

Overview

Formatting retrieved data into standardized JSON output with answer lists and token tracking.

Use Cases

  • Writing query results to JSON files
  • Formatting answers as lists regardless of count
  • Tracking API token consumption
  • Creating consistent output files for downstream processing

Required Output Format

{
    "q1": {"answer": ["xxx"], "tokens": 123},
    "q2": {"answer": ["xxx", "yyy"], "tokens": 456},
    "q3": {"answer": [], "tokens": 789}
}

Code Examples

Initialize Result Container

import json

result = {
    "q1": {"answer": [], "tokens": 0},
    "q2": {"answer": [], "tokens": 0},
    "q3": {"answer": [], "tokens": 0}
}

Add Single Answer

def add_answer(result, question_key, answer_items, tokens=0):
    """Add answer as list (always list format)"""
    # Ensure answer_items is a list
    if isinstance(answer_items, str):
        answer_items = [answer_items]
    elif not isinstance(answer_items, list):
        answer_items = list(answer_items)

    result[question_key] = {
        "answer": answer_items,
        "tokens": int(tokens)
    }
    return result

# Usage
result = add_answer(result, "q1", ["eid_1e9356f5"], tokens=150)
result = add_answer(result, "q2", employee_ids_list, tokens=200)

Write to JSON File

import json

def write_result_file(result, filepath):
    """Write result to JSON file"""
    with open(filepath, 'w') as f:
        json.dump(result, f, indent=4)
    print(f"Results written to {filepath}")

# Usage
write_result_file(result, '/root/answer.json')

Track Token Usage (Without API)

import json

# For local data processing, estimate tokens
def estimate_tokens_from_text(text):
    """Rough estimation: ~4 characters per token"""
    return len(text) // 4

# Better: track actual API usage
def track_tokens(usage_dict):
    """Track from API response"""
    if hasattr(usage_dict, 'input_tokens'):
        return usage_dict.input_tokens + usage_dict.output_tokens
    return 0

Read the full file on GitHub · 174 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. 4d ago First seen · 174 lines · 16 tokens per session scan A c082bdf6d4aa

Subscribe to this mod's changes

json-result-formatting is a skill published in the GitHub repository cxcscmu/SkillLearnBench (82 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 1,182 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 2026-08-30.

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