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Official agent skill

Meridian Result Visualization

by google in google/meridian

Loads a saved Meridian MMM model and produces an HTML results summary, with optional health checks and approval checkpoints at each step.

OfficialApache-2.0Auto-check passedData & Analytics

Install Meridian Result Visualization

skills CLI
$ npx skills add google/meridian --skill meridian-result-visualization -a claude-code

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

GitHub CLI
$ gh skill install google/meridian meridian-result-visualization --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/google/meridian.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/meridian_result_visualization .claude/skills/meridian-result-visualization && 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
meridian-result-visualization
GitHub stars
1.6k
Token cost
~1.3k tokens
SKILL.md length
568 words
Files
4 (incl. references)
Skills in repo
5
Repo updated
First seen
Licence
Apache-2.0

At a glance

Loads a saved Meridian MMM model and produces an HTML results summary, with optional health checks and approval checkpoints at each step.

  • Works in 6 steps: Initial Setup → Add Model Loading Code → Add Post-Modeling Health Checks Code… → …
  • Loading a saved Meridian model to look at its performance and fit
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Generating the Model Results Summary report as an HTML file

What it does

This skill walks the agent through a fixed workflow for viewing the results of a fitted Meridian model. It first asks you for the path to the serialized model (meridian_model.binpb by default), where to save the results_summary.html report, where to write the generated Python script, and any report options such as date ranges.

The agent then adds code that loads the model with meridian_serde.load_meridian(), optionally adds post-modeling health checks through reviewer.ModelReviewer that save to HTML, and builds the Model Results Summary. At every step marked as a critical checkpoint it shows the proposed paths or code and waits for your answer to a multiple-choice question, even if you asked it to work autonomously. Reference files cover model loading, health checks and the summary. Budget optimization and model fitting belong to other skills.

When your agent uses it

  • Loading a saved Meridian model to look at its performance and fit
  • Generating the Model Results Summary report as an HTML file
  • Running post-modeling health checks on a fitted model

Example prompts

  • “Load meridian_model.binpb and generate the results summary report.”
  • “Run the health checks on my fitted Meridian model and save them to HTML.”
  • “Show me how well my saved Meridian model fits, limited to a date range I will give you.”

Requirements

  • A fitted Meridian model saved as a serialized file
  • Python with the Meridian package installed

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Initial Setup
  2. Add Model Loading Code
  3. Add Post-Modeling Health Checks Code (Optional)
  4. Add Model Results Summary Code
  5. Pre-execution Checkpoint
  6. Execution & Script Setup

What it can do on your machine

Read from SKILL.md and the folder at commit 88a4434. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Meridian Result Visualization loads about 1.3k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 91 tokens; SKILL.md has 568 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

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 google/meridian at commit 88a4434, republished under its Apache-2.0 licence (© google). 568 words, ~1,250 tokens.

Download SKILL.mdSave it as .claude/skills/meridian-result-visualization/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
meridian-result-visualization
description
Loads a fitted Meridian model and generates standard visualization reports: Model Results Summary. Use when the user wants to load a saved model and view results (model performance, fit, health). Don't use for running budget optimization (use meridian-budget-optimization) or building/fitting the model (use meridian-model-building).

Meridian Result Visualization

A skill for loading a fitted Meridian model and generating standard visualization reports.

Core Workflow

Interactivity Checkpoint Rule

Throughout this workflow, you will encounter CRITICAL INTERACTIVE CHECKPOINTs. At each checkpoint, you MUST:

  1. Present the current proposed configurations, report paths, script path, or status to the user for approval.
  2. Ask the user if they are ready to proceed using the available user-interaction tool (e.g., ask_question), structured as a multiple-choice question. Do NOT use raw chat text.
  3. Wait for their response before proceeding.
    • MANDATORY: You MUST pause at every checkpoint regardless of the initial prompt instructions (even if the user request contains phrases like "run autonomously", "execute directly", "fix autonomously", etc.). The initial request does NOT bypass these interactive checkpoints.
    • Note: If the user replies to a checkpoint with a generic approval (e.g., "proceed", "do what you think is best"), proceed with the proposed defaults.
1. Initial Setup
  • Prompt the user for the path to the serialized model file (meridian_model.binpb by default).
  • Prompt the user for output paths for:
    • Model Results Summary report (results_summary.html by default).
  • Prompt the user for the desired path for the generated Python script.
  • Prompt the user for any optional configuration for the reports (e.g., date ranges for results summary).
  • CRITICAL INTERACTIVE CHECKPOINT: Present the gathered paths and configurations to the user and obtain confirmation before loading the model.
2. Add Model Loading Code
  • Use meridian_serde.load_meridian() to load the model.
  • See load_model.md for code template.
  • CRITICAL INTERACTIVE CHECKPOINT: Present the model load path configuration and proposed Python code snippet to the user, and obtain approval before continuing to specify health checks.
3. Add Post-Modeling Health Checks Code (Optional)
  • Use reviewer.ModelReviewer to run health checks and save to HTML.
  • Small / Test Models: If a model has fewer than 2 MCMC draws (e.g. test or mock models where R-hat computation requires >= 2 samples), catch ValueError or skip R-hat calculation gracefully so health check reports generate cleanly.
  • See health_check.md for code template.
  • CRITICAL INTERACTIVE CHECKPOINT: Present the proposed health check report path and code snippet to the user, and obtain approval before continuing to results summary configuration.
Show full SKILL.md (216 more words)Show less
4. Add Model Results Summary Code
  • Use summarizer.Summarizer to generate the HTML results summary, applying any user-specified configuration (e.g., date ranges).
    • Date Range Auto-Clipping: If applying a user-specified date range falls outside the model's time coordinates, clip or adjust the date range to match the model's actual coordinates.
    • Tip for errors: If you encounter errors regarding sample_prior, bypass or fix the requirement (for example, by setting sample_prior=False or passing the required parameters) to ensure successful generation.
  • See results_summary.md for code template.
  • CRITICAL INTERACTIVE CHECKPOINT: Present the proposed date ranges, output path configuration, and code snippet for the results summary to the user, and obtain approval before proceeding to script generation and execution.
5. Pre-execution Checkpoint
  • CRITICAL INTERACTIVE CHECKPOINT: Present the final report path and script path to the user, and ask for final confirmation to execute the results generation script now.
6. Execution & Script Setup
  • Write the accumulated Python script to the user-specified path. When writing the file using write_to_file, explicitly set ArtifactMetadata.RequestFeedback=false to avoid pausing execution.
  • Execute the script using Python: prefer the active virtual environment if available (e.g. .venv/bin/python3 or /tmp/meridian_eval_cache/bin/python3, otherwise python3).
  • CRITICAL: Do NOT delete the generated reports, the script, or the output directory at the end of the task. These are the deliverables requested by the user and must be preserved.

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in skills/meridian_result_visualization of google/meridian.

  • SKILL.md
  • references/health_check.md
  • references/load_model.md
  • references/results_summary.md

Open the folder on GitHubat commit 88a4434

Compare with similar skills

Meridian Result Visualization 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.

Meridian Result Visualization compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Meridian Result Visualization this skillgoogle/meridian1.6k—~1.3kAutomated safety check: PassApache-2.0
Looker Studiothatrebeccarae/claude-marketing162—~3.6kAutomated safety check: NotesMIT
Scientific Figure MakingChenLiu-1996/figures4papers8.2k—~557Automated safety check: PassCustom licence
Plot From ImageTrae1ounG/paper-plot-skills8661 repos~868Automated safety check: PassNone
Python Executorcortega26/chile-hub1132 repos~1.5kAutomated safety check: PassMIT
FigMirror Figure Style TransferVILA-Lab/FigMirror523—~2.1kAutomated safety check: PassNone

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Works with

Categories

Questions about Meridian Result Visualization

What does Meridian Result Visualization do?

Loads a saved Meridian MMM model and produces an HTML results summary, with optional health checks and approval checkpoints at each step. This skill walks the agent through a fixed workflow for viewing the results of a fitted Meridian model.html report, where to write the generated Python script, and any report options such as date ranges.

When should I use Meridian Result Visualization?

Meridian Result Visualization fits situations like: loading a saved Meridian model to look at its performance and fit; generating the Model Results Summary report as an HTML file; running post-modeling health checks on a fitted model.

How do I install Meridian Result Visualization in Claude Code?

Run `npx skills add google/meridian --skill meridian-result-visualization -a claude-code`. Or copy the skill folder (skills/meridian_result_visualization in google/meridian) into .claude/skills/meridian-result-visualization in your project. Claude Code loads it when a task matches its description.

How do I install Meridian Result Visualization in Codex?

Run `npx skills add google/meridian --skill meridian-result-visualization -a codex`. Or copy the skill folder (skills/meridian_result_visualization in google/meridian) into .agents/skills/meridian-result-visualization in your project. Codex loads it when a task matches its description.

Can I use Meridian Result Visualization 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 google/meridian --skill meridian-result-visualization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meridian-result-visualization, .gemini/skills/meridian-result-visualization, .github/skills/meridian-result-visualization and .opencode/skills/meridian-result-visualization in your project.

What does Meridian Result Visualization need to run?

SKILL.md names no scripts, command-line tools or credentials: Meridian Result Visualization is instructions for the agent only. Our summary lists: A fitted Meridian model saved as a serialized file; Python with the Meridian package installed.

Does Meridian Result Visualization access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Meridian Result Visualization 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 Meridian Result Visualization use?

Meridian Result Visualization is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Meridian Result Visualization use?

About 1.3k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 334 tokens, read only when the agent opens those files.

What are the alternatives to Meridian Result Visualization?

Skills that share tags, products or a category with Meridian Result Visualization: Looker Studio (thatrebeccarae/claude-marketing, 162 stars), Scientific Figure Making (ChenLiu-1996/figures4papers, 8.2k stars), Plot From Image (Trae1ounG/paper-plot-skills, 866 stars) and Python Executor (cortega26/chile-hub, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meridian Result Visualization?

google (a GitHub organization, an official publisher) maintains it in google/meridian, which has 1,558 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 7, 2026.

Source: google/meridian on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.