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check_sources

Verify alignment between website catalog, installed kit, and paired app versions to detect drift and ensure consistent control surface behavior.

Instructions

Report where the MCP is pulling truth from, and flag any drift.

CAR-TER's MCP is a thin local tool layer over live sources: control DEFINITIONS come from the website catalog (carterbeaudoin.net/CAR-TER), and authoring DEMOS come from the installed carterkit. This shows the catalog version/freshness/fingerprint, installed-vs-latest carterkit, and — when a device is paired — the phone's app/protocol version, then gives an alignment verdict.

Run this at the start of a session, and again whenever a pushed layout behaves unexpectedly, to catch the case where the site, the kit, and the app have drifted out of sync.

Args: refresh: Force a fresh fetch of the website catalog + PyPI version, bypassing the local cache.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refreshNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, but description fully discloses behavioral traits: shows catalog version/freshness/fingerprint, installed-vs-latest carterkit, phone app version when paired, and alignment verdict. Also explains caching behavior and refresh action.

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

Conciseness4/5

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

Description is well-structured with clear purpose, explanation of sources, usage guidance, and argument. Slightly verbose but every sentence adds value.

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

Completeness5/5

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

Given the tool has an output schema and the description explains return values conceptually, the description is complete. It covers usage context, parameter, and behavioral output without missing critical information.

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

Parameters5/5

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

The single parameter 'refresh' is described in detail in the description: 'Force a fresh fetch of the website catalog + PyPI version, bypassing the local cache.' This compensates for 0% schema description 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?

Description clearly states the tool reports on MCP truth sources and flags drift, using specific verbs 'report' and 'flag' with distinct resources (catalog, carterkit, phone app). No sibling tool has similar purpose.

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?

Explicitly says when to use: 'at the start of a session' and 'whenever a pushed layout behaves unexpectedly'. Does not explicitly state when not to use or alternatives, but given sibling list, no other tool serves this diagnostic role.

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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