VarynForge

List article suggestions

list_article_suggestions

Read-only

List article suggestions for a project — title, status, priority, cluster, intent, source, publishedAt, scheduledFor, and a per-channel distributions rollup ({ channel, count, latestAt, scheduledFor } per channel the content went out on). Use distributions to spot gaps from the list alone — e.g. items with no linkedin entry have no LinkedIn post yet — without per-item reads. Page through suggestions; call get_article_suggestion for the full record. Status semantics: generating_brief with briefQueuedAt set means the brief is QUEUED behind the free daily cap and forges automatically at cap reset (get_article_brief returns queuedUntil); generating_brief with briefQueuedAt null means it is actively forging — re-check within a minute.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	Yes
`cursor`	No
`status`	No
`context`	Yes	One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.
`projectId`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed2 schema fields changedSep 4, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "projectId",
-  "limit"
-]New value: +[
+  "projectId",
+  "limit",
+  "context"
+]

First observedAug 3, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only behavior is covered. The description adds useful behavioral context beyond annotations: the status semantics for generating_brief (briefQueuedAt set vs null), automatic forging at cap reset, and the recommendation to re-check within a minute. This helps the agent interpret returned statuses correctly.

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 dense but every sentence earns its place: return fields, practical gap-spotting use, paging/full-record routing, and status disambiguation. It is front-loaded with the core action and well organized from general to specific.

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?

Despite having no output schema, the description explains the main return shape including the nested distributions rollup, defines status semantics that affect interpretation, and covers pagination and the relationship to the detail tool. This is sufficient for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema description coverage is only 20%, so the description carries most of the semantic burden. It clarifies projectId by saying 'for a project', cursor via 'Page through suggestions', and status via the detailed status semantics. Limit is self-explanatory and documented in the schema. The context parameter is already described in the schema, so this is reasonable compensation.

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 opens with a specific verb and resource: 'List article suggestions for a project' and enumerates exact returned fields, including the distributions rollup shape. It clearly differentiates from get_article_suggestion by saying to call that tool for the full record, so an agent can distinguish 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 Guidelines5/5

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

Explicitly tells when to use this tool vs. the alternative: use the list and its distributions rollup to spot gaps 'without per-item reads', and page through suggestions rather than fetching individually. It also directs to get_article_suggestion for full records, giving clear routing guidance.

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 target a distinct resource and action, and the descriptions carefully cross-reference close alternatives (e.g., add_article_suggestion vs create_article_suggestion_with_input vs accept_idea). A few brief/read variants like get_article_brief, get_write_handoff, and download_brief_markdown could still be confused despite helpful explanations, so the set is not perfectly unambiguous.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun snake_case pattern throughout: get_*, list_*, create_*, update_*, set_*, add_*, delete_*, start_*, expand_*, etc. Even the less common names like lint_draft and remap_asset are still clear verb_noun constructions.

Tool Count1/5

At 57 tools, this far exceeds the 50+ extreme threshold for a single MCP server. Even for a broad content workflow, the surface is overwhelming and would benefit from consolidation or splitting into focused servers.

Completeness4/5

The tool set covers the full content lifecycle: project setup, research runs, opportunity clustering, suggestion creation, brief generation, drafting, linting, publishing, reporting, and account management. Minor gaps exist—destinations and projects cannot be deleted via MCP, and there is no direct update for article suggestion metadata—but these are workable via the web UI or existing tools.

Resources

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