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Submit feedback to Bucky

submitBuckyFeedback
Idempotent

Open a human-reviewed feedback form and submit it to the Bucky product team. Call only when the user explicitly asks to send feedback, report a problem, suggest an improvement, or praise something. The server asks the MCP client to show the form; nothing is saved unless the human accepts it. Do not use for silent agent self-reporting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
submissionIdYesA new UUID generated for this submission. Reuse the same UUID when retrying this exact feedback.
affectedToolNameNoTool the user is commenting on, when already known

TDQS

A4.4/5.0
Behavior4/5

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

The description adds meaningful behavioral context beyond annotations: the server asks the MCP client to display a form, and 'nothing is saved unless the human accepts it.' This clarifies the human-in-the-loop, conditional-persistence behavior, which the idempotent/readOnly/destructive hints alone do not convey. There is no contradiction with the annotations.

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 three tight sentences, each with a distinct job: state the core action, define trigger conditions, and describe the persistence behavior. The most identifying information is front-loaded, and there is no redundant restatement of any schema fields.

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

Completeness4/5

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

The description covers the key invocation context: user must explicitly request feedback, the flow is human-reviewed, and unattended self-reporting is prohibited. It also hints at the interactive output ('server asks the MCP client to show the form') even without an output schema. It could specify what the client should do once the human accepts, but the essential selection and invocation information is present.

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%, so the baseline is 3. The description itself adds no parameter-level guidance; all details about the context field's word count and third-person requirement, the submissionId UUID pattern, and affectedToolName are in the schema. The tool description does not compensate further, so the baseline stands.

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: 'Open a human-reviewed feedback form and submit it to the Bucky product team.' This clearly distinguishes it from the analysis/project sibling tools, none of which handle feedback. It leaves no ambiguity about what the tool accomplishes.

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?

It explicitly limits invocation to 'when the user explicitly asks to send feedback, report a problem, suggest an improvement, or praise something' and forbids 'silent agent self-reporting.' These are concrete when-to-use and when-not-to-use rules. Even though no alternative tool is named, no sibling covers feedback, so the guidance is sufficient.

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

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: explanation, guide, snapshot, context, report, analysis run, save, feedback, status check, and update. The only overlap is between getProjectContext and uiGetAnalysisStatus, but the description explicitly clarifies that getProjectContext is preferred, making the distinction unambiguous.

Naming Consistency5/5

All tool names follow a consistent lowerCamelCase verb_Noun pattern (e.g., getFeasibilitySnapshot, runFeasibilityAnalysis, produceProjectReport). Minor variations like saveToProject and uiGetAnalysisStatus still adhere to the same structural style, so naming is predictable and uniform.

Tool Count5/5

With 10 tools, the server covers the full project lifecycle—lookup, creation, analysis, reporting, status, updates, and feedback—without redundancy or bloat. The count is well-scoped for the stated domain of property feasibility analysis.

Completeness4/5

Core workflows are covered: create project, attach lots/references, run analysis, retrieve context, update metadata, and generate reports. Major gaps include no list-projects operation and no delete/archive capability, though the documentation explicitly notes these are unsupported on this surface, making them expected limitations rather than operational dead ends.

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