Agent skill

Investigate Data

by walkthru-earth in walkthru-earth/geocoding-playground

Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP.

CC-BY-4.0Auto-check passedData & Analytics

Install Investigate Data

skills CLI
$ npx skills add walkthru-earth/geocoding-playground --skill investigate-data -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install walkthru-earth/geocoding-playground investigate-data --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/walkthru-earth/geocoding-playground.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/investigate-data .claude/skills/investigate-data && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
investigate-data
GitHub stars
153
Token cost
~935 tokens
SKILL.md length
260 words
Files
1
Skills in repo
2
Repo updated
First seen
Licence
CC-BY-4.0

At a glance

Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP.

  • Works in 7 steps: Understand the issue: What country, what… → Check the schema first if unsure about… → Query the relevant index using… → …
  • The user reports a bug in autocomplete results
  • SKILL.md covers S3 Base URL, Workflow, Known Gotchas and Parquet Verification Queries
  • Reaches s3.us-west-2.amazonaws.com

What it does

Investigate Data is an agent skill from walkthru-earth/geocoding-playground. Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP. Use this skill when the user reports a bug in autocomplete results, duplicate entries, missing data, wrong city/street/postcode results, or asks to check data for a specific country. Also use when the user says 'check the data', 'investigate', 'query S3', 'what does the index look like', 'how many streets/cities/postcodes', or 'verify the data'. Do NOT use for frontend UI bugs, build issues, or code refactoring.

Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering DataFrames, File uploads and storage and Frontend development. It works with Model Context Protocol and DuckDB. The repository describes itself as: Browser-based geocoder powered by DuckDB-WASM and Overture Maps, 469M+ addresses, zero backend. The licence is CC-BY-4.0.

When your agent uses it

  • The user reports a bug in autocomplete results
  • Duplicate entries
  • Wrong city/street/postcode results
  • Asks to check data for a specific country

Example prompts

  • “check the data”
  • “investigate”
  • “query S3”
  • “/investigate-data”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob, mcp__motherduck__execute_query

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Understand the issue: What country, what index, what unexpected behavior?
  2. Check the schema first if unsure about columns
  3. Query the relevant index using MotherDuck MCP (mcpmotherduckexecute_query)
  4. Diagnose the root cause using these patterns
  5. Simulate the fix by running the corrected query and verifying output.
  6. Cross-validate by checking 2-3 other countries for the same pattern.
  7. Report with

What it can do on your machine

Read from SKILL.md and the folder at commit d16cf53. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • mcp__motherduck__execute_query

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are sql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • s3.us-west-2.amazonaws.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Investigate Data loads about 935 tokens when it runs. Until then it costs about 132 tokens; SKILL.md has 260 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~132
When it runs · the whole SKILL.md, loaded when a task matches
~935

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from walkthru-earth/geocoding-playground at commit d16cf53, republished under its CC-BY-4.0 licence (© walkthru-earth). 260 words, ~935 tokens.

Download SKILL.mdSave it as .claude/skills/investigate-data/SKILL.md (or your agent's skills folder).
name
investigate-data
description
Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP. Use this skill when the user reports a bug in autocomplete results, duplicate entries, missing data, wrong city/street/postcode results, or asks to check data for a specific country. Also use when the user says 'check the data', 'investigate', 'query S3', 'what does the index look like', 'how many streets/cities/postcodes', or 'verify the data'. Do NOT use for frontend UI bugs, build issues, or code refactoring.
allowed-tools
Read, Grep, Glob, mcp__motherduck__execute_query

Data Investigation Skill

Investigate geocoder data issues by querying live parquet files on S3.

S3 Base URL

https://s3.us-west-2.amazonaws.com/us-west-2.opendata.source.coop/walkthru-earth/indices/addresses-index/v4/release=<RELEASE>/

Substitute the current release, newest is 2026-04-15.0 as of 2026-04-18. The app auto-discovers releases, so never hard-code an old one.

Workflow

  1. Understand the issue: What country, what index, what unexpected behavior?

  2. Check the schema first if unsure about columns:

    sql
    DESCRIBE SELECT * FROM read_parquet('...BASE_URL.../city_index/country=XX/data_0.parquet') LIMIT 1;
  3. Query the relevant index using MotherDuck MCP (mcp__motherduck__execute_query):

    • City issues: city_index/country=XX/data_0.parquet
    • Street issues: street_index/country=XX/data_0.parquet
    • Postcode issues: postcode_index/country=XX/data_0.parquet
    • Number issues: number_index/country=XX/data_0.parquet
    • Tile data: geocoder/country=XX/h3_res4=HEXHASH/bucket=NN/data_0.parquet
    • Global stats: manifest.parquet, tile_index.parquet
  4. Diagnose the root cause using these patterns:

    • Duplicates: GROUP BY key_cols HAVING count(*) > 1
    • Missing data: SELECT count(*) FILTER (col IS NULL)
    • Tile overlap: list_has_any(tiles, [expected_tiles])
    • Merged rows: Check bbox span (bbox_max - bbox_min) for unreasonably large values
    • Ambiguity: Check len(tiles) distribution for a street name
  5. Simulate the fix by running the corrected query and verifying output.

  6. Cross-validate by checking 2-3 other countries for the same pattern.

  7. Report with:

    • Root cause (which pipeline step or data source)
    • SQL evidence (the queries and results)
    • Recommended fix (upstream pipeline SQL or frontend query-time dedup)

Known Gotchas

  • IT, JP, TW, CO have no postcode_index (404)
  • FR has no region (depth-1 address_levels only)
  • JP numbers in raw Overture are "banchi-coordZone", pipeline strips the zone suffix
  • City index uses per-country flat files, not global
  • Multi-unit buildings (apartments) emit one row per unit with identical full_address, the only differentiator is the unit column. 195 Clearview AVE in Ottawa = 328 rows. Always SELECT unit when investigating apparent duplicates

Parquet Verification Queries

After pipeline rebuilds, verify Parquet optimization with:

sql
-- number_index: should have many small row groups + bloom filters
SELECT num_rows, num_row_groups, file_size_bytes
FROM parquet_file_metadata('...BASE_URL.../number_index/country=NL/data_0.parquet');

-- Bloom filters present?
SELECT path_in_schema, bloom_filter_offset, bloom_filter_length
FROM parquet_metadata('...BASE_URL.../number_index/country=NL/data_0.parquet')
WHERE path_in_schema = 'street_lower' LIMIT 5;

-- Geocoder tile bloom filters on street?
SELECT path_in_schema, bloom_filter_offset
FROM parquet_metadata('...BASE_URL.../geocoder/country=NL/h3_res4=841969dffffffff/bucket=_/data_0.parquet')
WHERE path_in_schema = 'street' LIMIT 3;

© walkthru-earth, CC-BY-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/investigate-data of walkthru-earth/geocoding-playground.

Open the folder on GitHubat commit d16cf53

Compare with similar skills

Investigate Data next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Investigate Data compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Investigate Data this skillwalkthru-earth/geocoding-playground153—~935Automated safety check: PassCC-BY-4.0
Querying Big Datasetsflyrank-bih/flyrank-ml-internship-starter140—~750Automated safety check: PassCustom licence
Data Cleaningericrisco/rsc-harness180—~3.6kAutomated safety check: PassMIT
Pandas ProJeffallan/claude-skills12k1 repos~1.5kAutomated safety check: PassMIT
Retentioneering Product Analyticsretentioneering/retentioneering-tools927—~1.6kAutomated safety check: PassApache-2.0
Webapp Buildersidequery/sidemantic129—~5.5kAutomated safety check: PassAGPL-3.0

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Questions about Investigate Data

What does Investigate Data do?

Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP. Investigate Data is an agent skill from walkthru-earth/geocoding-playground. Investigates geocoder data quality issues by querying live S3 parquet files via MotherDuck MCP.

When should I use Investigate Data?

Investigate Data fits situations like: the user reports a bug in autocomplete results; duplicate entries; wrong city/street/postcode results; asks to check data for a specific country.

How do I install Investigate Data in Claude Code?

Run `npx skills add walkthru-earth/geocoding-playground --skill investigate-data -a claude-code`. Or copy the skill folder (.claude/skills/investigate-data in walkthru-earth/geocoding-playground) into .claude/skills/investigate-data in your project. Claude Code loads it when a task matches its description.

How do I install Investigate Data in Codex?

Run `npx skills add walkthru-earth/geocoding-playground --skill investigate-data -a codex`. Or copy the skill folder (.claude/skills/investigate-data in walkthru-earth/geocoding-playground) into .agents/skills/investigate-data in your project. Codex loads it when a task matches its description.

Can I use Investigate Data in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add walkthru-earth/geocoding-playground --skill investigate-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/investigate-data, .gemini/skills/investigate-data, .github/skills/investigate-data and .opencode/skills/investigate-data in your project.

What does Investigate Data need to run?

SKILL.md names no scripts, command-line tools or credentials: Investigate Data is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, mcp__motherduck__execute_query.

Does Investigate Data access the network?

SKILL.md names 1 domain. In commands or code: s3.us-west-2.amazonaws.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Investigate Data safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Investigate Data use?

Investigate Data is published under the CC-BY-4.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Investigate Data use?

About 935 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Investigate Data?

Skills that share tags, products or a category with Investigate Data: Querying Big Datasets (flyrank-bih/flyrank-ml-internship-starter, 140 stars), Data Cleaning (ericrisco/rsc-harness, 180 stars), Pandas Pro (Jeffallan/claude-skills, 12k stars) and Retentioneering Product Analytics (retentioneering/retentioneering-tools, 927 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Investigate Data?

walkthru-earth (a GitHub organization) maintains it in walkthru-earth/geocoding-playground, which has 153 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on June 24, 2026.

Source: walkthru-earth/geocoding-playground on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.