ingest_text

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that the tool writes to the Neo4j knowledge graph and triggers insight generation, indicating side effects. However, it does not mention reversibility, idempotency, or failure modes, and the description stops short of outlining any permissions or rate limits.

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

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

The description is well-structured with a clear purpose statement, numbered pipeline steps, and an Args section. The numbered steps provide a logical flow, but the overall length is slightly verbose—some steps could be condensed without losing meaning. The purpose is front-loaded, which is good.

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

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

The tool is moderately complex with three parameters, one required, and no output schema provided. The description covers the main pipeline and return type, but lacks details on expected text format, size limits, error handling, or the structure of the returned summary. Given that an output schema is declared as present (though not shown), the description could reasonably delegate return details, but it leaves gaps around constraints and edge cases.

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

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

Schema description coverage is 0%, so the description must compensate. It does so by listing each parameter (text, source, metadata) with a short explanation of its purpose (raw text, provenance, additional metadata). This adds meaningful context beyond the schema's type/default information, though the descriptions are brief and do not specify formats or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool ingests and processes text into a knowledge graph via semantic analysis, with a concrete resource and verb. It lists specific pipeline steps (Montague Grammar, entity extraction, Neo4j storage) that distinguish it from generic 'ingest' tools, though it does not explicitly name sibling tools like wiki_ingest_raw or synapse_remember to highlight differences.

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

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

No guidance is provided on when to use this tool versus alternatives. The description explains what it does but lacks any conditional context, such as 'use this for raw text ingestion' or exclusions like 'for structured data, use query_knowledge'. An agent must infer appropriate usage from the resource name alone.

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