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ingest_diagram

Parse architecture or flow diagrams (Mermaid, PlantUML, DOT, or text) into structured semantic fragments for context memory, making diagram knowledge retrievable via optimization and recall.

Instructions

Ingest an architecture or flow diagram into the context memory.

Converts Mermaid, PlantUML, DOT/Graphviz, or informal diagram text into a structured semantic fragment capturing nodes, edges, and relationships. The result is stored as a normal context fragment and is retrievable by optimize_context and recall_relevant.

Args: diagram_text: Raw diagram source (Mermaid/PlantUML/DOT/text description). source: Identifier (e.g., 'arch_overview.mmd', 'db_schema.puml'). diagram_type: 'mermaid', 'plantuml', 'dot', 'text', or 'auto' (default).

Returns JSON with ingestion result (same as remember_fragment).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
diagram_textYes
diagram_typeNoauto

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains the conversion to a structured fragment, storage, and retrieval via other tools. It does not mention side effects or limitations but is sufficiently transparent.

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 concise and well-structured: a summary paragraph followed by a clear argument list. Every sentence adds value, and the format aids readability.

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 explains the conversion, storage, and retrieval process. It references the output format as 'same as remember_fragment', and since an output schema exists (per context signals), the description does not need to detail return values. It is adequately complete.

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

Parameters5/5

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

Schema coverage is 0%, so the description provides essential meaning. It defines each parameter: 'diagram_text' as source text, 'source' as identifier, and 'diagram_type' with enum values. This fully compensates for the schema's lack of descriptions.

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's action: 'Ingest an architecture or flow diagram into the context memory.' It specifies the input formats (Mermaid, PlantUML, etc.) and distinguishes itself from sibling tools like 'remember_fragment' by focusing on diagram conversion.

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?

The description implies usage for diagrams that need structured representation, but does not explicitly state when not to use it or compare with alternatives like 'remember_fragment'. However, the context is clear enough for an agent to determine appropriate use.

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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