Validate JSON-pointer and array projections by testing them locally against sample data before applying them to TRMNL projects.
Test declarative JSON-pointer and array projections locally against supplied sample data.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| fields | Yes |
Changes observed during successful MCP inspections.
v0.2.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety bar is lower. The description contributes the meaningful trait that evaluation happens locally against sample data (no server round-trip), but says nothing about what happens with malformed pointers, whether errors are reported per-field, or what the result looks like.
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?
A single tight sentence with the key qualifier 'locally' and the subject 'declarative JSON-pointer and array projections' front-loaded. No filler, though the sentence could carry one more clause of operational detail at no cost to clarity.
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?
No output schema exists, so the description must convey what a test returns (pass/fail, projected output, error locations) — it does not. Combined with fully undocumented parameters and no error semantics, an agent can infer the intent but not how to format inputs or interpret results.
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?
Schema description coverage is 0% and both parameters are required; 'data' is completely untyped and 'fields' is an opaque nested object. The description only loosely maps 'data' to sample input and implies 'fields' holds JSON-pointer/array projection definitions, but gives no format, example, or expected shape — insufficient compensation for the coverage gap.
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?
Specific verb 'Test' plus resource 'declarative JSON-pointer and array projections' tells the agent exactly what operation is performed. The 'locally' qualifier and the mention of sample data distinguish it from remote evaluation siblings like trmnl_project_validate, though the sibling list contains no similarly named projection tool to contrast against.
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?
Usage is only implied: 'locally against supplied sample data' suggests this is a dry-run/preview step, presumably before applying projections elsewhere. There is no explicit when-to-use/when-not, and no named alternative among the many trmnl_* siblings is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.