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mcp_engram_thought_tile_create

Create a structured Thought Tile for agent memory in formats like research offload, state machine, or knowledge graph, with automatic linking to the primary intent.

Instructions

Create a new Thought Tile (textual functor payload optimized for agent recall, momentum, NREM, and ki_hijacker). Supports research_offload, state_machine, tabular, knowledge_graph, formal_spec and similar agent-first-principles tiles. Pair with thought_tile_create_visualization for rich human-viewable companion. Auto-links to Primary Intent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goal_contextNoOptional explicit goal. If omitted, auto-links using primary_goal + recent active goal logic (same as record_reasoning_trace).
parent_tileNoOptional parent tile for decomposition / result hierarchy
payloadYesStructured JSON payload matching the schema for the chosen tile_type
process_contextNoOptional process:engram.* key — emits realized_by edge (WS-3)
spatial_referencesNoOptional list of existing concept names (spatial AST nodes, ritual anchors, etc.) this Tile compresses or references. Creates compresses_path / compresses_chain_from relations for trace:* refs.
tile_typeYesresearch_offload | state_machine | tabular | knowledge_graph | formal_spec | html_visualization | verified_sequence
titleYesShort human-readable title for the tile
Behavior3/5

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

No annotations exist, so the description carries the burden. It discloses the auto-linking to Primary Intent, which is a behavioral trait. However, it does not explain side effects, input validation, or what happens on failure, limiting transparency.

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 sentences, front-loads the core purpose, and each sentence adds unique value: definition, supported types, and pairing advice. No wasted words.

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?

Given 7 parameters and no output schema, the description covers the main purpose and supported types but omits expected return values (e.g., tile ID). Schema coverage fills parameter details, but output behavior is missing.

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 coverage is 100%, so the baseline is 3. The description adds minimal parameter semantics beyond the schema—it lists supported tile types (already in tile_type description). It does not explain payload structure or spatial_references format.

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 names the tool ('Create a new Thought Tile') and specifies its purpose as optimized for agent recall and supporting specific tile types. It differentiates from the visualization sibling by suggesting pairing, but does not explicitly distinguish from other creation siblings like thought_tile_draft_from_chain.

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?

The description implies usage by listing supported tile types and recommending pairing with the visualization tool, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among the many sibling tools.

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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