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

No annotations are provided, so the description carries full burden. It discloses the DETACH DELETE behavior (detach parameter) but lacks details on irreversibility, required permissions, or impact on related data. Moderate transparency.

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 extremely concise: one introductory line plus a compact bullet list of parameters. Every sentence is necessary and no information is redundant or verbose.

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?

Given the output schema exists, the description adequately explains inputs. However, it could mention the return type (e.g., number of deleted nodes) or error cases. Still sufficient for a delete operation with a clear pattern.

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?

All three parameters (label, match_properties, detach) are explained in the description, adding clear meaning beyond the input schema (which has 0% coverage). The docstring provides explicit definitions and usage hints.

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 verb 'delete' and the resource 'nodes' with matching criteria (label + match_properties). It unambiguously distinguishes from sibling tools like neo4j_insert, neo4j_update, and neo4j_query.

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?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no conditions for using the detach parameter. It simply describes the operation without contextual direction.

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

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

With no annotations, the description must disclose behavior. It only states the action (creating a node) but omits side effects (e.g., duplicate handling), authorization needs, or output expectations.

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 extremely concise with no wasted words. The purpose is front-loaded in the first sentence, and the parameter descriptions are brief yet functional.

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?

For a simple node creation tool with an output schema, the description covers basics but lacks details like idempotency, constraints, or return behavior. It is minimally viable but not comprehensive.

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?

The description adds examples for 'label' and clarifies 'properties' as key-value pairs, but schema coverage is 0% and the improvements over the schema are minimal. Baseline 3 applies due to low coverage and two parameters.

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 'Create a node in Neo4j', combining a specific verb with a resource. It distinguishes from sibling tools like neo4j_insert_relationship (relationships) and neo4j_query (read operations).

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 (e.g., when to create a node vs. a relationship). No exclusions or prerequisites are mentioned.

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

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

No annotations are provided, so the description must cover behavioral traits. It only states that the relationship is created between existing nodes, but does not disclose what happens if nodes are not found, whether the operation is idempotent, or any side effects. This is insufficient for safe invocation.

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 concise, uses a clear docstring format, and front-loads the action. The Args section is efficient, though not every sentence is essential. No wasted words.

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?

An output schema exists, so return value documentation is not required. However, the description lacks information on error handling, constraints (e.g., relationship uniqueness), and success indicators. It is minimally complete for a tool with 6 parameters and no annotations.

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 explains each parameter's purpose, notes that from_properties and to_properties must be unique, and clarifies rel_properties is optional. This adds significant meaning beyond the raw schema.

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 verb 'create' and the resource 'relationship', and specifies that nodes are matched by label and properties. It distinguishes from siblings like 'neo4j_insert' (creates nodes) and 'neo4j_search_relationships' (searches relationships).

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?

The description implies the tool should be used when creating a relationship, but does not provide explicit guidance on when to use it versus alternatives (e.g., neo4j_insert for nodes, neo4j_update for modifying nodes). No exclusion criteria or prerequisites are mentioned.

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

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

While no annotations are provided, the description warns of arbitrary execution and explains the 'write' parameter for write queries. It does not disclose rate limits or auth needs, but for a direct query tool, the caution is sufficient.

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 concise: a one-line summary, a warning, preference guidance, then argument details. It is well-structured and front-loaded with critical information.

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?

Given the presence of an output schema, the description covers purpose, when to use/avoid, parameter details, and safety warnings. It provides all necessary context for an AI agent to invoke the tool correctly.

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 coverage is 0%, but the description explains each parameter in the Args section: query as Cypher string, parameters as optional, write as boolean for write operations. This adds significant meaning beyond the schema's minimal type info.

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 explicitly states 'Execute a raw Cypher query against Neo4j.' This clearly defines the tool's function and distinguishes it from structured sibling tools like neo4j_search and neo4j_insert.

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?

The description includes a warning about arbitrary Cypher execution and explicitly advises 'Prefer the structured tools when possible.' This provides clear when-to-use and when-not-to-use guidance, naming specific alternatives.

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

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

With no annotations, the description carries full burden. It discloses the tool's output but does not mention behavioral traits like non-destructiveness or performance considerations. For a simple read-only introspection tool, this is adequate but not exemplary.

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 two sentences, front-loaded with the main action, and contains no unnecessary words. Every sentence adds value.

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?

Given no parameters and an expected simple output (labels, relationship types, etc.), the description is fully complete for an agent to understand what the tool does and what it returns.

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?

The tool has no parameters, so the description need not add parameter details. The baseline score of 4 is appropriate as there is no omission.

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's purpose: 'Introspect the Neo4j database schema' and specifies what it returns (labels, relationship types, indexes, constraints). It is easily distinguishable from sibling tools like neo4j_query or neo4j_insert which handle data manipulation.

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 explicit guidance on when to use this tool versus alternatives. While it is obvious that schema introspection differs from data operations, the description does not provide any when-to-use or when-not-to-use hints.

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

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

No annotations exist, so the description carries the burden. It explains search types and limit defaults, but omits details like case sensitivity, response structure, or error behavior. Output schema may cover return format, but not fully compensating.

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 concise and well-structured: purpose first, then usage alternatives, then parameter list. Every sentence adds value, no redundancy.

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?

Considering the tool's complexity (two modes, 4 params) and no annotations, the description is fairly complete. It lacks details on return format (though output schema exists) and error handling, but overall covers essential usage.

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 coverage is 0%, so description fully compensates. It explains each parameter's purpose, expected format (e.g., exact match dict, LIKE query), and constraints (default 25, max 100). This adds significant value beyond schema types.

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 searches for Neo4j nodes, with two distinct modes: label+properties or query. It distinguishes from siblings like neo4j_search_relationships and neo4j_query.

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?

It provides explicit guidance on using one of the two modes (label+properties or query), but does not explicitly exclude alternatives or mention when not to use this tool over siblings.

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

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

No annotations are present, so the description carries the full burden. It discloses the search pattern and filter capabilities, and mentions limit defaults/maximums. However, it does not describe side effects, permissions, or behavior when no results are found, leaving some transparency gaps.

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 one-line summary, the pattern, and an Args list. It is appropriately front-loaded. A minor improvement could be consolidating repeated references to the pattern, but overall it is clear and not verbose.

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?

Given an output schema exists, the description adequately covers search inputs without needing to detail return values. It provides all necessary filter information but could mention edge cases like empty results or handling of null property filters for full completeness.

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?

The input schema has no property descriptions (0% coverage), so the description adds full meaning for all 6 parameters: from_label, from_properties, rel_type, to_label, to_properties, and limit (with default and max). This is critical for correct tool use.

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 searches for relationships (edges) in Neo4j, specifying the exact pattern (from_node)-[rel]->(to_node). This distinguishes it from sibling tools like neo4j_search (which likely searches nodes) and neo4j_query (general Cypher queries).

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?

The description implies usage for finding relationships matching filters, and sibling names provide context (e.g., neo4j_search for nodes). However, it does not explicitly state when to use this tool vs alternatives, nor does it mention prerequisites or exclusions.

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

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

No annotations provided, so the description must disclose behavioral details. It states 'Update properties' but does not specify if it overwrites entire properties, handles partial updates, or what happens if multiple nodes match. Missing mutation semantics and side effects.

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 very concise, front-loading the core purpose and listing parameters in a structured Args format. Every sentence is valuable, no redundancy.

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 description covers the basic purpose and parameter roles, but lacks behavioral context (e.g., idempotency, multiple node handling). With an output schema present, return value details are not required, but usage guidelines and behavioral transparency are incomplete.

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?

Despite 0% schema description coverage, the description's Args section clearly explains each parameter's role (label to match, properties to identify nodes, properties to set). This adds meaning beyond the schema's simple titles and types.

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 updates properties on nodes matching a label and match_properties, specifying the verb and resource. It distinguishes from sibling tools like neo4j_delete or neo4j_insert, which serve different purposes.

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 explicit guidance on when to use this tool versus alternatives. It implies usage for updating existing nodes, but lacks context on when to choose this over neo4j_search (to find nodes) or neo4j_query (for arbitrary updates).

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