Outrings Web Intelligence

Generate an embeddable verification badge

get_badge_embed

Read-onlyIdempotent

Produce the HTML (and Markdown) for a badge the site owner can paste into their footer or README. It renders a live SVG showing a real measured score that refreshes every six hours and links through to the full audit, so a visitor can verify it. Use this when someone wants to display that their site was checked.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes	The website to inspect. A bare domain works — "example.com" is treated as https://example.com.
`style`	No	Badge shape. score shows the number, verified shows a tick and wordmark, shield is the flat two-part style used by build badges, compact is the smallest.	score
`theme`	No	Colour scheme to match the page it will sit on.	light
`metric`	No	Which score the badge displays. Use overall unless the site wants to highlight one category.	overall

Output Schema

TableJSON Schema

Name	Required	Description
`host`	Yes
`html`	Yes	Ready-to-paste anchor and image markup.
`linkUrl`	No	Full report the badge links to, so a visitor can verify the score.
`imageUrl`	Yes	Live SVG badge; re-renders from a real audit every six hours.
`markdown`	No	The same badge for a README.

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations (readOnly, idempotent, non-destructive), the description adds that the badge is a live SVG that refreshes every six hours and links to the full audit, which is valuable for setting user expectations about behavior. This is meaningful additional context without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences: the first front-loads the action and output, the second gives usage context. No filler or redundant phrasing, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a relatively simple tool, the description covers the output format, live behavior, refresh rate, linkage, and usage trigger. With a full schema and output schema present, it doesn't need to explain return values further. It could mention limitations (e.g., public accessibility requirement) but is otherwise complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers 100% of parameters with descriptive text for each (url, style, theme, metric). The description does not add parameter-specific semantics beyond the schema, so baseline 3 is appropriate for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it produces HTML (and Markdown) for an embeddable verification badge, specifying the output format and target user (site owner). This distinguishes it from sibling tools like get_score (which returns a numeric score) by focusing on the embeddable code artifact.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this when someone wants to display that their site was checked,' providing a clear trigger condition. It does not explicitly mention alternatives or exclusions, but this context is sufficient to guide selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes: full audit vs. single-category check vs. score-only vs. comparison vs. badge embed vs. inventory vs. change tracking. However, check_ai_visibility overlaps with check_category's 'ai' area, potentially causing confusion for agents. Descriptions help delineate but the overlap is notable.

Naming Consistency4/5

Seven of eight tools follow a consistent verb_noun snake_case pattern (audit_website, check_ai_visibility, check_category, compare_websites, get_badge_embed, get_score, get_site_inventory). Only 'what_changed' breaks the pattern by using a question phrase. Otherwise naming is uniform and predictable.

Tool Count5/5

8 tools is well-scoped for a website intelligence server. Each tool addresses a distinct need (full audit, narrow check, AI visibility, comparison, score, badge, inventory, diff tracking) without being excessive or sparse. The set feels complete for its domain.

Completeness5/5

The tool surface covers the full lifecycle of analyzing a website: comprehensive audit (audit_website), granular category checks (check_category, check_ai_visibility), score retrieval (get_score), comparison (compare_websites), change monitoring (what_changed), asset inventory (get_site_inventory), and even a sharing artifact (get_badge_embed). No obvious dead ends or missing operations for the stated purpose.

Resources

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