Validate arbitrary JSON against an optional JSON Schema. Output: { valid: boolean, errors?: array }.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | JSON value to validate | |
| schema | No | Optional JSON Schema draft-07 |
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 and idempotentHint, so the description does not need to restate side-effect safety. The description adds useful behavioral context by disclosing the exact output shape: '{ valid: boolean, errors?: array }', which is not present in annotations or an output schema.
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?
The description is one dense, front-loaded sentence followed by a compact output-shape note. There is no filler or redundant information.
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?
For a simple validation tool with full schema descriptions and safety annotations, the description is mostly complete. It could clarify that the 'json' parameter is typed as an object in the schema despite saying 'arbitrary JSON', but the return-shape disclosure and optional-schema note give the agent enough to invoke it correctly.
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 covers 100% of parameters with descriptions, so the baseline is 3. The description adds only the 'optional JSON Schema draft-07' nuance and does not significantly extend what the schema already communicates.
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 uses the specific verb 'Validate' and identifies the resource as 'arbitrary JSON against an optional JSON Schema', making the tool's purpose immediately clear. None of the sibling tool names relate to JSON validation, so there is no risk of confusion.
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 description clearly states when to use the tool: to validate JSON, optionally against a schema. It does not explicitly name alternatives or exclusions, but no sibling tool is similar enough to require that guidance.
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.