VarynForge

Send feedback

send_feedback

File a note to the VarynForge team: a bug, a missing capability, a friction point, or an operator idea. Call when you hit something VarynForge cannot do, a confusing tool result, or the operator voices frustration or a wish. Whenever the task would benefit from a capability this tool list does not offer, file a missing_capability BEFORE you settle for a workaround with existing tools, even if they could work as a fallback. Do NOT file entitlement walls (PAYMENT_REQUIRED / RATE_LIMITED / FEATURE_LOCKED payloads) — those are working as designed. Feedback is a note to the team, never a ticket: do not promise the operator it will be fixed. There is no reply — read get_changelog over the following days to see whether the gap closed.

Input Schema

TableJSON Schema

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

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: -[
-  "kind",
-  "summary"
-]New value: +[
+  "kind",
+  "summary",
+  "context"
+]

First observedAug 3, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations only declare readOnlyHint=false and destructiveHint=false, which is thin. The description adds crucial expectations: feedback is not a ticket, no reply is produced, fixes must not be promised, and entitlement-wall payloads are working as designed. These behavioral details are not visible in the annotations or schema.

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 long but every sentence earns its place: it front-loads the core purpose, then covers when-to-use, what kind to file, exclusions, the no-promise policy, and the follow-up path. No filler or redundancy.

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?

For a six-parameter tool with no output schema and minimal annotations, the description supplies the missing operational envelope: no reply, how to verify outcomes later via get_changelog, and what not to submit. It leaves some parameter-level specifics to the schema but fully covers selection, invocation, and post-call expectations.

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 only 17% (only context is described), so the description carries the burden. It adds real meaning for kind by naming the four values and specifying when missing_capability should be used, but it does not explain summary, detail, projectId, or toolContext beyond what the schema shows. Partial compensation for a large gap.

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?

States a specific action ('File a note to the VarynForge team') and enumerates the four accepted kinds (bug, missing capability, friction, idea). The 'never a ticket / no reply' distinction differentiates it from support or inquiry tools, so an agent can identify its role without opening the schema.

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?

Gives explicit when-to-call triggers ('something VarynForge cannot do', 'confusing tool result', 'frustration or a wish') and an explicit when-not-to-call exclusion (entitlement walls). It also tells the agent to prefer missing_capability over workarounds and points to get_changelog for follow-up.

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.

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