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Northern Forge MCP

golden_hour_windows

Compute approximate sunrise/sunset/golden-hour windows for lat/lon/date (no API key). MVP solar math.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude
lonYesLongitude
dateNoISO date YYYY-MM-DD (default today UTC)

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It does state that the calculation is 'approximate' and based on 'MVP solar math', which hints at simplified accuracy. However, it does not disclose output format, timezone handling, edge cases (e.g., polar regions), or error behavior. The 'no API key' note adds operational context but is insufficient for full transparency.

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?

The description is a single concise sentence followed by a brief context note ('MVP solar math'). It is front-loaded with the core action, and every word contributes meaning. There is no redundancy or fluff, making it an example of efficient communication.

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

Completeness3/5

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

The tool is relatively simple with three parameters, all documented in the schema. However, there is no output schema, so the description should ideally clarify the return format and any default behavior. It does not mention that 'date' defaults to today UTC, nor what the output structure looks like. While the core purpose is clear, these gaps prevent a higher score.

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?

Schema description coverage is 100%, with each parameter having a description (lat, lon, date). The tool description merely mentions 'lat/lon/date' without adding further semantic details like units, coordinate format, or date interpretation. Since the schema already documents these parameters, the description adds minimal value, meeting the baseline of 3.

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 the tool's function: 'Compute approximate sunrise/sunset/golden-hour windows for lat/lon/date'. It uses a specific verb ('Compute'), identifies the resource (solar windows), and lists the primary inputs. It also adds a differentiating note ('no API key', 'MVP solar math') that distinguishes it from potential external services, making its purpose unambiguous even among sibling tools.

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

Usage Guidelines3/5

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

The description implies a use case through 'no API key' and 'MVP solar math', suggesting it's for quick, approximate calculations without external dependencies. However, it does not explicitly state when to use this tool over alternatives or provide exclusions. There are no direct sibling alternatives, but the guidance is implicit rather than explicit, thus scoring a 3.

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

B3.3/5.0
Disambiguation3/5

Most tools are clearly distinct, but there is overlap between local ops tools (gbrain_get/list/search, host_memory_get/set, forge_loop_status, list_mesh_snapshot, etc.) and public status/product tools (forge_status, popular_tools) which could confuse an agent. Descriptions help by tagging local ops, but the boundaries remain blurred.

Naming Consistency4/5

All tool names use snake_case and mostly follow a verb_noun or noun_verb pattern (e.g., get_product, list_live_products, csv_to_markdown). A few names like now_iso and lorem_ipsum deviate from the verb-first style, but overall the naming is predictable and consistent.

Tool Count2/5

With 40 tools, the server is overloaded for a coherent set. Many are simple utility functions that could be consolidated, and the mix of generic utilities, product APIs, and local ops adds unnecessary bulk, pushing the count well above the comfortable range.

Completeness2/5

The server lacks a clear domain, making it impossible to assess lifecycle coverage. While it offers many utilities, there is no coherent surface—missing common operations for any single category (e.g., no CRUD, no file handling) and many tools feel randomly assembled rather than forming a complete workflow.

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