Generate a 1200×630 Open Graph image URL for social previews. Output: HTTPS URL to rendered PNG.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Primary headline (max 120 chars) | |
| template | No | ||
| description | No | Subtitle (max 200 chars) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds that the result is a URL to a rendered PNG, but it does not disclose other behavioral traits such as rendering time, URL lifetime, or external service dependencies. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no filler. The purpose and output are front-loaded, and every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description states the output format (HTTPS URL to PNG) and the social-preview use case, while the schema and annotations cover parameters and safety. It is adequate for a simple generation tool, though a note about template effects or failure modes would be a minor enhancement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for 'title' and 'description', and the only undocumented parameter, 'template', has self-explanatory enum values. The tool description does not add meaning beyond the schema, but the 67% schema coverage plus readable enum names make this adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and a precise resource ('1200×630 Open Graph image URL'), and clarifies the output form ('HTTPS URL to rendered PNG'). This clearly differentiates the tool from siblings like forgekit_capture_screenshot and forgekit_render_pdf.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for social previews' establishes a clear use context. No explicit alternatives or exclusions are mentioned, but the tool's purpose is distinct enough that an agent can select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
ship_verify and ship_verify_v2 are near-synonyms, and ship_bundle wraps ship_pack plus an audit while evidence_pack combines screenshot/PDF/HTML. The descriptions help, but an agent could easily pick the wrong granularity or version.
All tools use the forgekit_ prefix and snake_case, but verb placement is inconsistent: business_days_add/count place the noun first, evidence_pack has no verb, and the ship_* group mixes noun and verb senses. The set is readable but not uniformly patterned.
Fifteen tools is near the upper end of a reasonable utility-kit size, and most tools are individually useful. It feels slightly over-scoped because ship_verify_v2 and ship_bundle partially duplicate other capabilities rather than adding clearly new operations.
The web/media surface is broadly covered with screenshots, PDFs, QR encode/decode, OG previews, evidence packs, and agent-readiness audits. However, the set is an eclectic collection rather than one coherent workflow, and there are gaps such as no MCP-level polling for async jobs and no history/retrieval for evidence packs or ship bundles.