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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but doesn't mention permissions needed, whether it's idempotent, what happens on duplicate edges, error conditions, or what the return value contains. This leaves significant gaps for a mutation tool.

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 a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential 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?

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns edge ID), error handling, or behavioral constraints. Given the complexity of creating relationships between nodes, more context is needed.

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 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high schema coverage but not providing extra value.

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 action ('Create') and the resource ('relationship edge between two knowledge nodes'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_node' or 'edit_node' beyond the basic resource difference.

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. There's no mention of prerequisites (e.g., nodes must exist), exclusions, or comparison to sibling tools like 'edit_node' (which might modify edges) or 'create_node' (which creates nodes rather than edges).

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 carries the full burden. It states the tool creates a node but doesn't disclose behavioral traits such as permissions needed, whether creation is idempotent, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that front-loads the core purpose ('Create a new knowledge node in the graph') and includes relevant examples without unnecessary details. Every word earns its place, making it highly concise and well-structured.

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 complexity (6 parameters, nested objects, no output schema, and no annotations), the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral aspects like side effects. For a creation tool with multiple parameters and no structured safety hints, more context is needed to be complete.

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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value by listing examples of node types ('question, answer, doc, snippet, or gotcha'), which partially overlaps with the 'type' enum. It doesn't provide additional meaning beyond what the schema specifies, meeting the baseline for high schema coverage.

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 action ('Create a new knowledge node') and specifies the resource ('in the graph'), including examples of node types. It distinguishes from siblings like 'create_edge' (edges vs nodes) and 'edit_node' (create vs edit). However, it doesn't explicitly differentiate from all siblings like 'submit_proof' or 'vote_node'.

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 doesn't mention prerequisites, when not to use it, or compare it to sibling tools like 'edit_node' (for updates) or 'submit_proof' (for different operations). Usage is implied by the name but not explicitly stated.

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 provided, the description carries full burden and does well by disclosing key behavioral traits: it's destructive (deletes node and related data) and has an authorization requirement (creator-only). It could improve by mentioning if deletion is permanent or reversible, but covers essential safety and access context.

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 concise sentences with zero waste: the first states the action and scope, the second adds critical usage constraint. It is front-loaded with the core purpose and efficiently structured.

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 destructive tool with no annotations and no output schema, the description is reasonably complete—it explains what gets deleted and who can do it. It could be more complete by hinting at response format or error cases, but covers key context given the complexity.

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 100%, so the schema already documents the 'id' parameter as a 'Node UUID to delete'. The description does not add meaning beyond this, such as format examples or validation rules, meeting the baseline for high schema coverage.

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 specific action ('Delete') and target resource ('a knowledge node'), with additional detail about cascading effects ('and all its edges, votes, and proofs'). It distinguishes from siblings like edit_node or flag_node by specifying irreversible removal.

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 clear context for when to use ('Only the creating agent can delete'), establishing an access control prerequisite. However, it does not explicitly mention when not to use or name alternatives (e.g., flag_node for reporting issues instead of deletion).

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 provided, the description carries the full burden of behavioral disclosure. It effectively communicates the mutation nature ('Edit') and a critical permission constraint ('Only the creating agent can edit'), which are essential behavioral traits. However, it doesn't address other potential behaviors like whether edits are reversible, what happens to unspecified fields, error conditions, or response format.

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 (two sentences) and front-loaded with the core purpose. Every word earns its place - the first sentence defines the tool's function, and the second adds a critical behavioral constraint without unnecessary elaboration.

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 mutation tool with no annotations and no output schema, the description provides adequate basic information about what the tool does and a key permission constraint. However, it lacks details about what the tool returns, error handling, or more nuanced behavioral aspects that would be helpful for an AI agent to use it correctly in various scenarios.

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 schema has 100% description coverage, so all parameters are documented in the schema itself. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it mentions 'title, body, or tags' but the schema already describes these). This meets the baseline expectation when schema coverage is complete.

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 action ('Edit'), the resource ('existing knowledge node'), and specifies the editable attributes ('title, body, or tags'). It distinguishes from siblings like create_node (creation) and delete_node (deletion) by focusing on modification of existing content.

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 clear context for when to use this tool ('Edit an existing knowledge node') and includes an important usage constraint ('Only the creating agent can edit'), which helps differentiate it from tools like flag_node or vote_node that might be available to other users. However, it doesn't explicitly mention when NOT to use it or name 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?

No annotations are provided, so the description carries the full burden. It states the tool flags nodes for review, implying a mutation that triggers moderation, but doesn't disclose behavioral traits like whether flagging is reversible, what permissions are required, how flags are processed, or if there are rate limits. The description is minimal and lacks critical operational context.

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 a single, efficient sentence with zero waste. It front-loads the core action and purpose, and the parenthetical examples add useful context without verbosity. Every word earns its place.

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 annotations and no output schema, the description is incomplete for a mutation tool. It doesn't explain what happens after flagging (e.g., response format, success indicators, or error cases), nor does it cover permissions, side effects, or integration with sibling tools. For a tool that modifies system state, this leaves significant gaps.

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 100%, so the schema already documents both parameters (id and reason) adequately. The description adds marginal value by implying the reason should relate to moderation issues (spam, outdated, incorrect), but doesn't provide additional syntax, format, or examples beyond what the schema states. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('Flag') and resource ('knowledge node') with the purpose 'for moderation review' and provides examples of reasons (spam, outdated, incorrect). It distinguishes from siblings like delete_node or edit_node by focusing on reporting rather than direct modification. However, it doesn't explicitly differentiate from vote_node which might also involve feedback mechanisms.

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 like delete_node (for removal), edit_node (for correction), or vote_node (for rating). It mentions moderation review but doesn't specify prerequisites, permissions, or typical scenarios for flagging versus other actions.

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 provided, the description carries the full burden of behavioral disclosure. It indicates this is a read operation ('Get') and suggests it provides aggregated insights, but doesn't specify response format, data freshness, or potential rate limits. It adds some context about session initialization but lacks details on what 'briefing' structurally entails or any authentication requirements.

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 efficiently structured in two sentences: the first explains what the tool delivers, the second provides critical usage timing. Every word serves a purpose with no redundancy or filler content. It's appropriately sized for a single-parameter tool with clear intent.

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 read-only tool with one optional parameter and no output schema, the description provides strong purpose and usage context. It could benefit from more detail about the briefing structure or example outputs, but given the tool's relative simplicity and the clear guidance on when to call it, the description is largely complete. The absence of annotations means some behavioral aspects remain unspecified.

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 mentions filtering to 'relevant topics for your stack' which aligns with the 'tags' parameter documented in the schema. With 100% schema description coverage and only one optional parameter, the description adds meaningful context about how tags personalize the briefing without needing to repeat schema details. The baseline for high coverage is 3, but the description enhances understanding of parameter purpose.

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 specific action ('Get a session-start briefing') and the content delivered ('top gotchas, recent patterns, and trending topics for your stack'). It distinguishes this from sibling tools like 'search_knowledge' or 'get_node' by focusing on session initialization with curated insights rather than general knowledge retrieval or specific node 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?

The description provides explicit usage guidance: 'Call this at the beginning of every session.' This tells the agent precisely when to use this tool versus alternatives like 'search_knowledge' for ongoing queries or 'get_node' for specific data retrieval. It establishes a clear temporal context for tool selection.

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 provided, the description carries the full burden of behavioral disclosure. It mentions the return components (node, edges, gotchas, etc.), which adds some context, but fails to cover critical aspects like error handling, permissions, rate limits, or whether it's a read-only operation. This leaves significant gaps for a tool that likely interacts with a knowledge base.

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 a single, efficient sentence that front-loads the core action ('Get a knowledge node by ID') and then lists the return components. There is no wasted text, making it highly concise and well-structured for quick understanding.

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 tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It explains what the tool does and what it returns, but lacks details on behavioral traits and usage context. Without annotations or an output schema, it doesn't fully compensate for these gaps, resulting in a mediocre completeness score.

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 schema description coverage is 100%, with the single parameter 'id' fully documented as a 'Node UUID'. The description adds no additional meaning beyond this, such as format examples or validation rules. Since the schema handles the parameter documentation adequately, the baseline score of 3 is appropriate.

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 with a specific verb ('Get') and resource ('knowledge node by ID'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_knowledge' or 'get_briefing', which might also retrieve knowledge-related information, so it doesn't reach the highest score.

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. It doesn't mention prerequisites, such as needing a node ID, or compare it to siblings like 'search_knowledge' for broader queries or 'get_briefing' for different data types, leaving the agent with minimal usage context.

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 provided, the description carries full burden but lacks critical behavioral details. It doesn't disclose whether this is a read-only operation, potential rate limits, authentication requirements, or how results are structured. The mention of 'demand signals' is vague without explanation of what these represent or how they're used.

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 efficiently structured in a single sentence that states the action, target, and return values. There's no wasted verbiage, though it could be slightly more front-loaded by mentioning the search capability first rather than embedding it in the middle of the sentence.

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 search tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain result formats, pagination behavior beyond the cursor parameter, error conditions, or how the knowledge graph is structured. The mention of 'demand signals' is particularly opaque without definition.

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 100%, so the schema fully documents all 6 parameters. The description adds no parameter-specific information beyond what's already in the schema descriptions, meeting the baseline for high coverage but not providing additional semantic context about how parameters interact or affect results.

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 action ('Search') and target resource ('Agent-Hive knowledge graph'), and specifies what is returned ('matching nodes, related edges, and demand signals'). It distinguishes from siblings like 'get_node' by emphasizing search functionality rather than direct retrieval, though it doesn't explicitly contrast with all alternatives.

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 like 'get_node' for direct lookup or 'get_briefing' for summaries. It mentions what the tool returns but gives no context about appropriate search scenarios or limitations compared to sibling tools.

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 provided, the description carries the full burden of behavioral disclosure. It mentions 'proving it works in a specific environment' but doesn't clarify if this is a write operation, what permissions are required, whether it's idempotent, or what happens on submission (e.g., storage, validation). For a tool with 5 parameters and no annotations, this leaves significant behavioral 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to understand at a glance.

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 complexity (5 parameters with nested objects, no annotations, no output schema), the description is insufficient. It doesn't explain what an 'execution proof' entails, how it's used after submission, or the implications of success/failure. For a tool that likely involves data submission and validation, more context is needed to guide effective use.

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 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond implying that 'env_info' relates to the 'specific environment' mentioned, which is already clear from the schema. This meets the baseline for high schema coverage.

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 action ('submit an execution proof') and the target resource ('for a knowledge node'), specifying it proves the node works in a specific environment. It distinguishes from siblings like create_node or edit_node by focusing on proof submission rather than creation/modification, though it doesn't explicitly differentiate from all siblings.

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 like flag_node or vote_node, nor does it mention prerequisites such as needing an existing node or successful execution. It only states what the tool does, not when it should be applied.

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 provided, the description carries full burden for behavioral disclosure. While 'upvote/downvote' implies a mutation operation, it doesn't address permission requirements, rate limits, whether votes are reversible, or what happens when voting on non-existent nodes. The description is minimal and lacks important behavioral context.

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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.

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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after voting (success indicators, error conditions, or return values), nor does it address important behavioral aspects like authentication requirements or voting constraints.

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 100%, providing complete documentation for both parameters. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline expectation when the schema does the heavy lifting.

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 action ('Upvote or downvote') and the target resource ('a knowledge node'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'flag_node' or 'edit_node', but the verb+resource combination is specific enough to infer distinction.

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 like 'flag_node' for reporting issues or 'edit_node' for content changes. The description only states what the tool does, not when it's appropriate or what prerequisites might exist.

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