data-filtering

data-filtering is a skill for Claude Code, Codex from cxcscmu/SkillLearnBench. It costs 14 tokens per session (1,251 once invoked), scanned A, original, MIT.

A guide for filtering travel records by conditions such as pet policies, price, location, amenities, cuisine, ratings, and attraction type.

In plain words
What is it for?
Filter hotels, restaurants, and attractions by trip needs and return matching records from Python data.
Why use it?
It narrows large lists to options that meet the traveller's actual requirements.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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/data-filtering
Any agent
npx skills add cxcscmu/SkillLearnBench --skill data-filtering
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 data-filtering

README.md
[![agentmods](https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/data-filtering.svg)](https://agentmods.dev/skills/cxcscmu/skilllearnbench/data-filtering)
Your own site
<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/data-filtering"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/data-filtering.svg" alt="Measured on agentmods" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,251 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 5.1 $0.00014 $0.01251
Opus 5 $0.00007 $0.00626
Sonnet 5 $0.00003 $0.00250
Haiku 4.5 $0.00001 $0.00125

Measured 2d ago against content hash b6d82fb61207, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

data-filtering 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.

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/travel-planning/data-filtering/SKILL.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Filtering Skill

Overview

Filter travel data by specific criteria like pet-friendly status, cuisine type, location, and price range.

Common Filter Scenarios

Accommodations

  • Pet-friendly filter
  • Price range (budget, mid-range, luxury)
  • Location (city, zip code)
  • Amenities (WiFi, parking, breakfast)

Restaurants

  • Cuisine type (American, Mediterranean, Chinese, Italian, etc.)
  • Location/city
  • Price range
  • Rating/reviews

Attractions

  • City location
  • Category (museum, park, historical, etc.)
  • Open during trip dates

Python Code Example

from typing import List, Dict
import re

def filter_pet_friendly_accommodations(
    accommodations: List[Dict],
    pet_friendly_field: str = 'pet_friendly'
) -> List[Dict]:
    """Filter accommodations that allow pets"""
    result = []
    for acc in accommodations:
        pet_field = acc.get(pet_friendly_field, '').lower()
        # Handle various formats: 'yes', 'true', '1', 'pet-friendly'
        if pet_field in ['yes', 'true', '1', 'pet friendly', 'pets allowed']:
            result.append(acc)
        elif 'pet' in pet_field and 'no' not in pet_field:
            result.append(acc)
    return result

def filter_by_cuisine(
    restaurants: List[Dict],
    cuisine_type: str,
    cuisine_field: str = 'Cuisine'
) -> List[Dict]:
    """Filter restaurants by cuisine type"""
    result = []
    cuisine_lower = cuisine_type.lower()

    for rest in restaurants:
        cuisines = rest.get(cuisine_field, '').lower()
        # Handle comma-separated cuisines
        if ',' in cuisines:
            cuisines_list = [c.strip() for c in cuisines.split(',')]
            if any(cuisine_lower in c for c in cuisines_list):
                result.append(rest)
        elif cuisine_lower in cuisines:
            result.append(rest)

    return result

def filter_by_city(
    data: List[Dict],
    city: str,
    city_field: str = 'City'
) -> List[Dict]:
    """Filter data by city"""
    result = []
    city_lower = city.lower()

    for item in data:
        item_city = item.get(city_field, '').lower()
        if item_city == city_lower:
            result.append(item)

    return result

def filter_by_price_range(
    data: List[Dict],
    min_price: float,
    max_price: float,
    price_field: str = 'Price'
) -> List[Dict]:
    """Filter data by price range"""
    result = []

    for item in data:
        try:
            price = float(item.get(price_field, 0))
            if min_price <= price <= max_price:
                result.append(item)
        except (ValueError, TypeError):
            continue

    return result

def filter_attractions_by_city(
    attractions: List[Dict],
    city: str,
    city_field: str = 'City'
) -> List[Dict]:
    """Filter attractions by city"""
    return filter_by_city(attractions, city, city_field)

def combine_filters(
    data: List[Dict],
    filters: Dict
) -> List[Dict]:
    """
    Apply multiple filters to data.
    filters dict: {'city': 'Cleveland', 'price_max': 100, ...}
    """
    result = data

    # Apply city filter
    if 'city' in filters:
        result = filter_by_city(
            result,
            filters['city'],
            filters.get('city_field', 'City')
        )

    # Apply price range filter
    if 'price_min' in filters or 'price_max' in filters:
        min_price = filters.get('price_min', 0)
        max_price = filters.get('price_max', float('inf'))
        result = filter_by_price_range(
            result,
            min_price,
            max_price,
            filters.get('price_field', 'Price')
        )

    # Apply cuisine filter
    if 'cuisine' in filters:
        result = filter_by_cuisine(
            result,
            filters['cuisine'],
            filters.get('cuisine_field', 'Cuisine')
        )

    return result

def select_diverse_options(
    data: List[Dict],
    num_selections: int,
    key_field: str = 'Name'
) -> List[Dict]:
    """Select diverse options avoiding duplicates"""
    seen = set()
    result = []

    for item in data:
        key = item.get(key_field, '').lower()
        if key not in seen:
            seen.add(key)
            result.append(item)
            if len(result) >= num_selections:
                break

    return result

Read the full file on GitHub · 201 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. 2d ago First seen · 201 lines · 14 tokens per session scan A b6d82fb61207

Subscribe to this mod's changes

data-filtering is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 1,251 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 2026-09-03.

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