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Glama

intentweave-mcp

submit_feedback

Submit user feedback for model improvement loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
ratingYes
lead_idYes
campaign_idNo
access_tokenNo
tenant_api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It only implies a write action but omits side effects, authentication requirements, idempotency, or response behavior. This is insufficient for an agent to anticipate impact.

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?

The description is a single, clear sentence that front-loads the verb and is appropriately brief. It is not padded, but it sacrifices potentially valuable context.

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

Completeness2/5

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

Given six parameters, including auth fields, and an output schema, the description is too sparse. It doesn't explain how feedback relates to leads/campaigns, what ratings mean, or the expected workflow, leaving critical ambiguities.

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

Parameters1/5

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

Schema description coverage is 0% and the description mentions no parameters. With six parameters, including sensitive ones like access_token and tenant_api_key, the agent receives no help understanding what to pass. The description entirely fails to compensate for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'Submit user feedback' and its purpose ('for model improvement loop'). It uses a specific verb and resource, though it doesn't explicitly differentiate from sibling tools beyond the name, which is distinct enough.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool instead of alternatives. It does not mention prerequisites, context (e.g., needing lead_id or rating), or how it relates to sibling tools like get_lead or run_campaign.

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

B3.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: cost estimation, bulk lead export, campaign status, single lead retrieval, vertical listing, campaign creation, and feedback submission. No two tools have overlapping purposes; even get_campaign and get_lead are clearly separated by campaign vs. lead granularity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (estimate_cost, export_leads, get_campaign, get_lead, list_verticals, run_campaign, submit_feedback). This is a uniform and predictable naming convention.

Tool Count5/5

The server has 7 tools, which is well within the ideal 3–15 range. Each tool serves a clear function in the campaign lifecycle without redundancy, making the count appropriate for the domain.

Completeness3/5

The server covers campaign creation (run_campaign), reading campaign status (get_campaign), lead access (get_lead, export_leads), cost estimation, and feedback. However, it lacks list_campaigns, update_campaign, and delete_campaign, which are notable gaps for managing multiple campaigns. The core workflow is usable but not a full CRUD surface.

Resources