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Antigravity Master MCP Gateway

Antigravity Master MCP Gateway

by ALDY711

sequential_thinking

Break down complex technical dilemmas into ordered reasoning steps, tracking each thought and deciding whether further analysis is needed.

Instructions

Jalankan alur kontemplasi nalar mendalam bertingkat (Sequential Thinking) untuk memecahkan dilema teknis rumit langkah demi langkah.

Input Schema

NameRequiredDescriptionDefault
thoughtYesLangkah pemikiran atau analisis saat ini
thoughtNumberYesNomor urut pemikiran (mulai dari 1)
totalThoughtsYesPerkiraan jumlah pemikiran yang dibutuhkan
nextThoughtNeededYesApakah masih membutuhkan pemikiran berikutnya?

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it says nothing about whether this call has side effects, whether state persists between invocations, how the thought/thoughtNumber loop is meant to terminate, or what the response contains. The critical behavioral trait of this pattern — that each call registers one step in a chain and the agent must repeat the call until nextThoughtNeeded is false — is left entirely undisclosed.

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?

A single front-loaded sentence with no redundancy or filler beyond a slightly ornamental adjective stack. It is efficient, though its brevity comes at the cost of the behavioral detail an agent actually needs.

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

Completeness3/5

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

For a four-required-parameter, no-output-schema, no-annotation tool, the schema fully covers parameter names and meanings, so the minimum is met. However, the iterative call-until-done protocol that defines correct invocation is missing from both the description and the annotations, leaving a real gap for an agent that must decide whether to call again.

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 all four required parameters are already documented in Indonesian in the schema itself. The description adds no additional meaning about how the parameters interact (for example, that thoughtNumber should increment monotonically or that totalThoughts is an estimate). Baseline 3 applies when the schema does the heavy lifting.

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 states a specific activity: step-by-step deep reasoning for solving complex technical dilemmas, and names the tool's mechanism (Sequential Thinking). It is clear what the tool is for, though the phrasing 'alur kontemplasi nalar mendalam bertingkat' is ornate rather than precise. No sibling tool overlaps with it, so no differentiation is required.

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

Usage Guidelines3/5

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

It gives implicit usage guidance by scoping the tool to 'dilema teknis rumit' (complex technical dilemmas) solved step by step, which tells an agent roughly when to reach for it. It never says when NOT to use it, nor does it contrast it with simply reasoning inline, and there are no explicit preconditions or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.