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VarynForge

Get onboarding guide

get_onboarding_guide
Read-only

Diagnose where the operator is in their VarynForge journey and get a guided setup path. Call when the operator asks to set up VarynForge, get started, or seems unsure what to do next — and always when list_projects returns empty. Returns the server-derived stage, a stage-tailored pitch to relay to the operator, a setup checklist with done/pending status per step, and the ranked next_actions queue. Diagnose before prescribing: never run the welcome pitch on an operator whose stage says producing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior4/5

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

Annotations provide readOnlyHint=true, and the description aligns by focusing on diagnosis and returning data. It adds nontrivial behavioral context: the tool returns server-derived stage, a pitch, a checklist with statuses, and next_actions queue, and explicitly warns against a specific misuse. It doesn't contradict annotations, and the description adds substance beyond the annotation's minimal read-only hint.

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 compact yet packed: purpose, trigger scenarios, alternative approach ('Diagnose before prescribing') and a direct warning. Every sentence serves a function, and the most important info (diagnosis, warning) is front-loaded.

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 no parameters, no output schema, and a readOnlyHint=true annotation, the description fully bridges the gap: it defines use cases, return fields, and the core rule (never welcome when producing). An agent can correctly invoke this without needing further explanation.

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?

Schema is empty (0 parameters) with 100% coverage by triviality, and the description explains that the tool requires nothing because it derives stage server-side. It adds meaning by explaining that no input is needed and what the tool infers (e.g., from list_projects emptiness), which is exactly what an agent needs to know when calling a parameterless tool.

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 definition states a specific purpose ('Diagnose where the operator is in their VarynForge journey and get a guided setup path'), identifies clear trigger conditions ('call when...'), and distinguishes from siblings by referencing list_projects and warns against using the welcome pitch when 'producing'. This is distinct from the other get_* tools in the sibling list.

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

Usage Guidelines5/5

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

Explicitly asks 'call when' scenarios and an exclusion ('never run the welcome pitch on an operator whose stage says producing'). This gives precise when-to-use and when-not-to-use guidance unlike most siblings.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but a few pairs could confuse an agent: add_article_suggestion vs create_article_suggestion_with_input, and get_article_brief vs download_brief_markdown vs get_write_handoff all deal with brief content. The detailed descriptions help disambiguate, but the overlap is real.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in lowercase snake_case (create_project, list_opportunities, generate_article_brief, lint_draft). There is no mixing of camelCase, acronyms, or vague verbs, making the naming predictable and readable.

Tool Count2/5

50 tools is excessive for an MCP server, even for a broad platform like content operations. While the scope is large, this many tools will overwhelm agents and increase latency and context cost. Most practical servers are well under 25.

Completeness4/5

The tool surface covers the full content lifecycle: project creation, research, opportunity clustering, content planning, briefs, drafting, linting, publishing, and reporting. Minor gaps exist (e.g., no delete_project, no remove_destination, no direct analytics beyond distributions), but they are workarounds or handled in the web UI.

Resources