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dioptx
by dioptx

AoT-full

Break down complex problems into atomic reasoning steps with decomposition-contraction at depth 5. Use for implementation plans, architecture decisions, and multi-step verification.

Instructions

Deep structured reasoning with decomposition-contraction. Depth 5.

Use for: implementation plans, architecture decisions, multi-step verification, problems that decompose into sub-problems.

Trigger phrases: "plan", "design", "megathink", "full AoT", /aot-plan.

Same atom types and parameters as AoT-fast. Drives decomposition via the atomcommands tool (decompose → sub-atoms → complete_decomposition). Reach for AoT-fast first unless you genuinely need the extra depth or decomposition.

viz param: only set viz:true when the user explicitly asks to see the graph or says "visualize". Never set it automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
atomIdYesUnique identifier for the atom (e.g., 'P1', 'R1', 'H1', 'C1')
contentYesThe thought content of this atom
atomTypeYesType of atom
dependenciesNoIDs of atoms this depends on (default: [])
confidenceNoConfidence 0-1 (default: 0.7)
isVerifiedNoWhether this atom has been verified
depthNoDepth level (auto-calculated if omitted)
vizNoRender and open a D3 visualization of the current graph after this atom (default: false). Set true during planning or when the user is reviewing your reasoning; leave false during execution.
sessionIdNoTarget session for this atom (default: active session). Sessions isolate atom graphs so two reasoning problems in one process don't collide. Use atomcommands new_session/switch_session to manage explicitly. Auto-spawned on next zero-dep atom after a session terminates.
Behavior4/5

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

No annotations are provided, so the description carries full burden. It explains the decomposition process via 'atomcommands' and the 'viz' parameter behavior. However, it does not specify what happens at the end of depth 5 (e.g., auto-termination or continuation), which is a minor gap.

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 well-structured with clear sections for purpose, usage, inter-tool comparison, and parameter notes. Every sentence adds value, and there is no unnecessary verbiage. It is concise yet informative.

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?

Given the tool's complexity (9 parameters, no output schema), the description covers all critical aspects: core functionality, usage conditions, important parameter nuances (sessionId, viz), and relationship to sibling tools. It is sufficiently complete for an agent to use correctly.

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

Parameters4/5

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

Schema coverage is 100%, providing a baseline of 3. The description adds useful context beyond the schema, particularly for 'sessionId' (explaining isolation and auto-spawning) and 'viz' (when to set it). This extra guidance is valuable.

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 clearly states the tool is for 'deep structured reasoning with decomposition-contraction' at 'Depth 5', and lists specific use cases and trigger phrases. It effectively distinguishes itself from the sibling 'AoT-fast' by noting it is used when extra depth or decomposition is needed.

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?

The description explicitly lists when to use the tool ('implementation plans, architecture decisions, multi-step verification, problems that decompose into sub-problems'), provides trigger phrases, and advises to use 'AoT-fast' first unless genuinely needing extra depth. This clearly guides the agent on selection.

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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