MR
Mayur Rathi
@sickn33
⭐ 47.3k GitHub stars

glasser

glasser is an data AI skill with a core value of Search, inspect, and run third-party data APIs through one CLI when the environment has no suitable integration. It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

Search, inspect, and run third-party data APIs through one CLI when the environment has no suitable integration.

Last verified on: 2026-10-06

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 47.3k
Last Verified 2026-10-06
Risk Level Low
mkdir -p ./skills/glasser && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/glasser/SKILL.md -o ./skills/glasser/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Glasser


Overview


Glasser is a commercial API broker that exposes third-party data providers

through one CLI and one account. Use it to fill a data gap after checking the

environment's free tools and the user's existing integrations. Provider output

keeps its native structure, so inspect the selected endpoint before every run.


This skill was contributed by a member of the Glasser team.


When to Use This Skill


- Use when a task needs current web, news, search, social, business, people,

places, shopping, image, video, or enrichment data that available tools

cannot supply.

- Use when the user wants pay-per-call access without creating a separate

account with the underlying provider.

- Use for marketing and research workflows that need structured evidence from

a named data provider.

- Prefer the user's explicit provider choice, existing API keys, installed

integrations, and free tools before Glasser.


How It Works


Step 1: Check Availability and Authentication


Use the CLI only if it is already installed or the user has approved its

installation under the host environment's software-installation policy.

Installation instructions are maintained at

<https://glasser.ai/SKILL.md>. Do not download or install executable code

without the review and approval required by the current environment.


Check the CLI and account:


bash
glasser --version
glasser balance

If authentication is missing in an interactive session, run `glasser login`.

It opens a browser-based device flow. Relay the URL and code printed by the CLI

and wait for the command to finish. Never ask the user to paste a Key into chat.


For unattended environments, the user can configure `GLASSER_API_KEY` through

the environment's secret manager. Never write it to a project file or include

it in a command argument.


Step 2: Discover Candidate Endpoints


Search by capability instead of guessing a provider or endpoint:


bash
glasser search -q "Google search results"
glasser search -q "company enrichment"
glasser search -q "Reddit posts and comments"

Compare the provider, endpoint, and listed price. Search results are ranked by

relevance; rank is not a quality or price recommendation.


Step 3: Inspect the Contract


Inspect the exact endpoint before constructing input:


bash
glasser inspect -p serper -e /search

Record:


- the current price and all charge clauses;

- required and optional input fields;

- fields that control result volume;

- run mode and timeout;

- the provider that will receive the request.


Schemas, prices, and charge clauses can change. The live `inspect` result is

the contract for the next run.


Step 4: Authorize the Paid Scope


Only `run` spends the workspace balance. Before the first paid call, show the

user the provider, endpoint, per-call price, charge exceptions, input scope,

and requested result volume. Wait for approval unless the user already gave an

exact scope or budget that covers the call.


Create the provider-native JSON input in a file after inspection. A file avoids

shell-quoting errors and keeps the request reviewable. Do not include unrelated

personal, confidential, or credential data.


Step 5: Run and Recover Safely


Run the approved request:


bash
glasser run -p serper -e /search -f request.json --wait

The CLI prints an Idempotency-Key. If a timeout or transport failure leaves the

outcome uncertain, repeat the request with that same key:


bash
glasser run -p serper -e /search -f request.json --idempotency-key <same-key> --wait

Do not create a new key for an ambiguous retry. It can create and charge a

second run. For a known run, use `glasser runs get -r <run-id> --wait` instead

of starting another one.


Step 6: Report Evidence and Cost


For every run used in the answer, report:


1. the provider and endpoint;

2. the Glasser run status;

3. what the provider response says;

4. the exact `Charge` printed by the CLI;

5. the private `Run URL` printed by the CLI.


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🎯 Best For

  • UI designers
  • Product designers
  • Claude users
  • Data professionals
  • Analytics teams

💡 Use Cases

  • Generating component mockups
  • Creating design system tokens
  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply glasser to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

Does this work with Figma?

Some design skills integrate with Figma plugins. Check the Works With section for supported tools.

How do I install glasser?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/glasser/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Skipping usability testing

AI-generated designs should be validated with real users before development.

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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