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Yggdrasil MCP

by henrychong-ai
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Sequential Thinking

sequential_thinking

Break down complex problems into adjustable thought steps, enabling revisions, branching, and hypothesis verification for multi-step analysis.

Instructions

A detailed tool for dynamic and reflective problem-solving through thoughts. This tool helps analyze problems through a flexible thinking process that can adapt and evolve. Each thought can build on, question, or revise previous insights as understanding deepens.

When to use this tool:

  • Breaking down complex problems into steps

  • Planning and design with room for revision

  • Analysis that might need course correction

  • Problems where the full scope might not be clear initially

  • Problems that require a multi-step solution

  • Tasks that need to maintain context over multiple steps

  • Situations where irrelevant information needs to be filtered out

Key features:

  • You can adjust total_thoughts up or down as you progress

  • You can question or revise previous thoughts

  • You can add more thoughts even after reaching what seemed like the end

  • You can express uncertainty and explore alternative approaches

  • Not every thought needs to build linearly - you can branch or backtrack

  • Generates a solution hypothesis

  • Verifies the hypothesis based on the Chain of Thought steps

  • Repeats the process until satisfied

  • Provides a correct answer

Parameters explained:

  • thought: Your current thinking step, which can include:

    • Regular analytical steps

    • Revisions of previous thoughts

    • Questions about previous decisions

    • Realizations about needing more analysis

    • Changes in approach

    • Hypothesis generation

    • Hypothesis verification

  • nextThoughtNeeded: True if you need more thinking, even if at what seemed like the end

  • thoughtNumber: Current number in sequence (can go beyond initial total if needed)

  • totalThoughts: Current estimate of thoughts needed (can be adjusted up/down)

  • isRevision: A boolean indicating if this thought revises previous thinking

  • revisesThought: If is_revision is true, which thought number is being reconsidered

  • branchFromThought: If branching, which thought number is the branching point

  • branchId: Identifier for the current branch (if any)

  • needsMoreThoughts: If reaching end but realizing more thoughts needed

You should:

  1. Start with an initial estimate of needed thoughts, but be ready to adjust

  2. Feel free to question or revise previous thoughts

  3. Don't hesitate to add more thoughts if needed, even at the "end"

  4. Express uncertainty when present

  5. Mark thoughts that revise previous thinking or branch into new paths

  6. Ignore information that is irrelevant to the current step

  7. Generate a solution hypothesis when appropriate

  8. Verify the hypothesis based on the Chain of Thought steps

  9. Repeat the process until satisfied with the solution

  10. Provide a single, ideally correct answer as the final output

  11. Only set nextThoughtNeeded to false when truly done and a satisfactory answer is reached

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thoughtYesYour current thinking step
branchIdNoBranch identifier
isRevisionNoWhether this revises previous thinking
thoughtNumberYesCurrent thought number (numeric value, e.g., 1, 2, 3)
totalThoughtsYesEstimated total thoughts needed (numeric value, e.g., 5, 10)
revisesThoughtNoWhich thought is being reconsidered
branchFromThoughtNoBranching point thought number
needsMoreThoughtsNoIf more thoughts are needed
nextThoughtNeededYesWhether another thought step is needed

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
branchesYes
thoughtNumberYes
totalThoughtsYes
nextThoughtNeededYes
thoughtHistoryLengthYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.11
    • changedInput schema / required
      Previous value: -[
-  "thought"
-]New value: +[
+  "thought",
+  "nextThoughtNeeded",
+  "thoughtNumber",
+  "totalThoughts"
+]
  2. First observedv1.2.6

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses important traits: thoughts can be revised, branched, or backtracked; total_thoughts is adjustable; the process generates and verifies a hypothesis; and the tool repeats until satisfied. It does not clarify side effects, state persistence, or whether the tool stores thought history across calls, which are relevant for a 9-parameter tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a good high-level summary, but it is lengthy and includes substantial repetition: the 'Key features' and 'You should' sections overlap heavily (e.g., revising thoughts, adding more thoughts, hypothesis generation/verification appear twice). This reduces conciseness and makes it harder to scan quickly.

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?

The description covers the purpose, usage scenarios, key features, and parameter meanings, which is fairly complete for a complex 9-parameter tool. However, with an output schema present, return value details are unnecessary; the main gap is the lack of sibling differentiation and clarification of state persistence, which would help an agent use it correctly in context.

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 schema already documents each parameter. The description provides additional interpretive guidance on the meaning of 'thought' (listing types of thinking steps) and elaborates on nextThoughtNeeded and totalThoughts. That adds some value, but much of the parameter explanation repeats the schema descriptions, so the baseline 3 is appropriate.

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 tool purpose ('dynamic and reflective problem-solving through thoughts') and describes the mechanism (sequential thoughts that can build, question, or revise). It is clear what the tool does, but it does not explicitly distinguish itself from siblings or clarify the MCP vs. conceptual nature. Sibling names like deep_planning suggest related planning tools, so more differentiation would help.

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

Usage Guidelines4/5

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

There is a clear 'When to use this tool' section listing several appropriate scenarios (breaking down complex problems, planning with revision, multi-step solutions, filtering irrelevant information). However, it does not state when not to use the tool or name alternatives among the siblings (e.g., deep_planning), which would make routing decisions more precise.

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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