Bungie

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

Annotations declare readOnlyHint, openWorldHint, and destructiveHint, covering safety and scope. The description adds that the tool internally routes to multiple tools and returns structured answers with citations, which is useful behavioral context beyond the annotations.

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 reasonably concise given the complexity. It front-loads the key preference statement and then provides examples and explanation. Every sentence serves a purpose, though a minor tightening could be achieved.

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 output schema, the description explains the return format (structured answer with citations). It covers when to use, what it does, and examples. It does not discuss error handling or rate limits, but for a query router with clear purpose, it is sufficiently 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?

The schema only defines 'question' as a natural language string. The description significantly enriches this by listing example queries (e.g., 'current US unemployment rate') and explaining how the question is used to select the appropriate tool and fill arguments, far exceeding the schema's minimal description.

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 routes questions to an extensive set of specialized data sources, providing a verb (ask), resource (2,353 tools, 559 sources), and scope (authoritative structured data). It distinguishes itself from web search and lists many example domains, making the purpose unmistakable.

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 explicitly says to prefer this tool over web search for factual, structured data questions and gives concrete query patterns (e.g., 'what is', 'look up', 'find'). It lacks an explicit when-not-to-use section, but the guidance is strong enough for most agentic scenarios.

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?

Discloses internal behavior: resolves market, classifies bet type, fans out to relevant data packs (e.g., crypto+fred+gdelt for BTC bets), and returns a comparison. Adds context beyond annotations (readOnly, openWorld), which already indicate safety.

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 comprehensive but slightly long. It front-loads the core purpose and then provides details. Every sentence carries value, though minor tightening could improve conciseness.

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 (multi-source research, classification, comparison), the description fully covers what the tool does, how it works, and usage context. No output schema but describes the output format adequately.

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 100% with descriptions. The description adds meaning by explaining input formats for 'market' and defining 'depth' values ('quick = 2-3 sources, thorough = full fan-out, default thorough').

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: research a Polymarket bet by pulling Pipeworx data, with specific input formats (slug, URL, question text) and output (evidence packet + market-vs-model comparison). It distinguishes itself from siblings by being the core demo product for bet research.

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?

Explicitly states when to use with example queries ('should I bet on X?', 'what does the data say...?', 'is there edge?'). It also implies that this is the preferred tool for bet context, contrasting with other tools that might require manual discovery.

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?

Annotations already indicate readOnlyHint and destructiveHint, and the description adds no behavioral context. The minimal phrase 'Character detail.' does not disclose any additional traits such as response format or authentication needs.

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 under-specified with only three words. While concise, it fails to convey essential information, making it ineffective rather than efficient.

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 four required parameters and no output schema, the description is entirely inadequate. It does not explain return format, parameter constraints, or how to use 'components'.

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% and the description provides no parameter details. With four required parameters and no compensation from the description, the agent cannot understand parameter meaning or values.

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 'Character detail.' is vague and lacks a specific verb. It does not clearly state that the tool retrieves character information, nor does it differentiate from sibling tools like 'profile' or 'equipped_loadout'.

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 on when to use this tool versus alternatives such as 'profile' or 'historical_stats'. The description provides no context for appropriate usage.

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?

Annotations already indicate read-only behavior, but description does not add context beyond 'detail'. It fails to disclose potential pagination, rate limits, or authentication needs.

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?

Extremely short but lacks a complete sentence structure; 'Clan/group detail.' is a fragment that saves no content over the tool name.

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?

Without output schema, description should describe what details are returned (e.g., name, member count, motto). It provides zero context, making the tool nearly opaque.

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?

With 0% schema description coverage, description should explain the 'group_id' parameter format and source, but merely implies it identifies the clan. Does not specify expected format or examples.

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?

Description identifies resource as 'clan/group' and indicates it provides details, but fails to distinguish from sibling tools like 'clan_members' or 'entity_definition' which also relate to groups.

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 on when to use this tool versus alternatives, nor any criteria for when it is appropriate or inappropriate.

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?

Annotations provide readOnlyHint=true and destructiveHint=false, so the safety profile is covered. However, description adds no behavioral context beyond annotations, such as pagination behavior, data freshness, or field explanations.

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 words long, which is overly terse. While concise, it lacks any structured information, such as action or resource clarification, making it unhelpful.

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 output schema and two parameters, the description should at minimum state the return type (list of members) and clarify parameter roles. It provides none of this, leaving the agent with insufficient context.

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%, but description does not explain what group_id represents (a clan identifier) or how current_page is used for pagination. Parameters are completely undocumented.

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?

Description 'Clan members' is a noun phrase with no verb, failing to indicate any action (list, get, search). It does not distinguish from sibling tool 'clan' which likely refers to the entity itself.

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 on when to use this tool versus alternatives like 'clan' or 'character'. No context on prerequisites or preferred use cases.

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?

Annotations declare read-only and non-destructive. Description adds detailed behavior: data sources for each type (SEC EDGAR/XBRL for companies, FAERS/FDA for drugs) and output includes citation URIs. No contradictions.

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?

Seven sentences efficiently cover purpose, usage triggers, per-type details, output format, and efficiency. Front-loaded with core functionality, no redundant 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?

Covers what, when, how, and output format for both entity types. No output schema, but description hints at return structure (paired data + URIs). Could be slightly more explicit about output fields, but sufficient for agent selection.

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 100%. Description enriches by specifying that 'values' requires tickers/CIKs for companies and drug names, and explains how 'type' affects data pulled. Adds practical detail beyond enum/array descriptions.

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 compares 2-5 companies or drugs side by side, with specific examples ("compare X and Y") and distinguishes from siblings like entity_profile by emphasizing multi-entity comparison.

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?

Provides strong positive guidance with concrete user query examples and efficiency note (replaces 8-15 sequential calls). Lacks explicit when-not-to-use cases, but context makes it clear this is for multi-entity comparison.

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?

Annotations already indicate read-only behavior, and the description adds that it returns the top-N most relevant tools with names and descriptions, providing useful behavioral context beyond the annotations.

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 front-loaded with the purpose and includes a list of example domains, which is slightly verbose but still efficient. It is well-structured and each 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?

For a tool discovery tool with no output schema, the description fully covers purpose, usage, parameters, and return format, providing complete context for an AI agent.

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 100% with descriptions for both parameters. The description adds value by linking 'top-N' to the limit parameter and providing example queries for the query parameter, enhancing understanding.

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 that this tool finds tools by describing the data or task, with specific verb 'Find tools' and resource 'tools' distinguished from sibling tools that perform specific domain actions.

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 explains when to use it ('browse, search, look up, discover') and advises calling it first for exploration, but does not explicitly state when not to use it, leaving some ambiguity.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, but the description adds no additional behavioral context (e.g., what happens if the definition is not found, whether it supports pagination, or how data is structured). With annotations present, the description provides minimal extra value.

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 short (five words) but lacks structure and fails to provide a complete sentence. While concise, it is under-specified and does not earn its place with useful 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?

The description is severely incomplete for a tool with 2 required parameters, 0% schema coverage, and no output schema. It provides no information about return values, error conditions, or parameter constraints, making it inadequate for proper agent 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% and the description does not explain what 'type' or 'hash_identifier' represent. The parameters are simply named without any semantic meaning or expected format, leaving the agent with no guidance beyond the parameter names.

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 states it returns a single definition by type and hash, which indicates the primary action and resource, but does not explain what a 'definition' is in this context, leaving some ambiguity. It vaguely distinguishes from siblings like 'entity_profile' but lacks specificity.

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 on when to use this tool versus alternatives like 'resolve_entity' or 'entity_profile'. The description is a single phrase with no context about appropriate usage scenarios.

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?

Annotations already indicate safe read-only behavior (readOnlyHint=true, destructiveHint=false). The description adds specific output details (SEC filings, revenue, patents, news, LEI, citation URIs) and confirms it's a single-call operation, supplementing annotations well. No contradictions.

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 few sentences) and front-loads the core purpose. Slightly verbose with the list of use cases but every sentence adds value. Could be tightened, but overall 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?

No output schema, but the description explicitly lists all return data types and mentions citation URIs. Given the tool's complexity (aggregating data from multiple sources), the description covers essential expectations. Minor gaps like pagination or error handling are not critical.

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 100%, and the description adds critical context: explains that type is only 'company' for now, and for value, it specifies ticker or CIK format with examples, plus advises using resolve_entity if only a name is available. This goes beyond the schema's basic descriptions.

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 'Get everything about a company in one call' with a specific verb and resource. It provides concrete example queries and distinguishes itself from siblings like resolve_entity and compare_entities, ensuring the agent understands its unique value.

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?

Explicitly describes when to use (e.g., when user asks 'tell me about X') and provides a key exception: names not supported, use resolve_entity first. Could be improved by stating when not to use (e.g., for single-data-point queries), but the guidance is clear and actionable.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds 'components=205' but does not explain its meaning or any behavioral traits beyond what annotations imply. Minimal additional 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 extremely short but omits essential information. It is under-specified rather than concise, offering no substantive value in a single cryptic phrase.

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 lack of output schema and low schema coverage, the description must compensate with richer detail. It fails to explain the tool's purpose, parameters, return values, or how components=205 is relevant. Incomplete for 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 0%, and the description provides no explanation of the three parameters (character_id, membership_type, destiny_membership_id). It fails to add meaning beyond the bare 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 'Equipped loadout (components=205)' is vague and mostly restates the tool name with an unexplained number. It does not clearly specify the verb or resource, nor differentiate it from siblings like profile or character that could also return loadout data.

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. Sibling tools exist (e.g., profile, character) that may also provide loadout information, but the description offers no usage context 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?

The annotations already indicate destructiveHint: true, so the description's disclosure of 'Delete' adds no new behavioral information. It provides usage context but not additional behavioral traits beyond what annotations supply.

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: the first states the action, the second provides usage guidance. It is efficient, front-loaded, and contains no superfluous content.

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 simplicity (one parameter, no output schema), the description covers purpose and usage adequately. It lacks details on error handling (e.g., missing key), but this is acceptable for a straightforward deletion tool with annotations already present.

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 'by key', aligning with the input schema's sole parameter. With 100% schema description coverage, the description adds no extra semantic value beyond the schema's existing parameter documentation.

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 'memory by key', making the tool's purpose explicit. It also distinguishes from siblings by mentioning pairing with 'remember' and 'recall'.

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 when-to-use guidance: 'when context is stale, the task is done, or you want to clear sensitive data'. It also indirectly suggests alternatives by referencing 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds no behavioral context beyond 'historical stats', such as authentication requirements, rate limits, or data scope. With annotations already covering safety, the description adds minimal value.

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, brief phrase that under-specifies the tool. It is not concise in a helpful way; it is too minimal to be useful. Every sentence should earn its place, but this one fails to provide necessary 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 tool has four parameters, no output schema, and sibling tools that likely share a domain, the description is completely inadequate. It does not explain the type of stats, how parameters affect output, or differentiate from similar tools. The description fails to provide a complete picture.

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 explain parameters. However, it does not mention any of the four parameters (modes, character_id, membership_type, destiny_membership_id). It provides no additional meaning beyond what the schema offers, which is just names 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 'Historical stats' is vague. It lacks a specific verb and resource, making it unclear whether the tool retrieves, processes, or performs some other action on historical stats. Sibling tool 'historical_stats_for_account' suggests a more specific scope, but this description does not differentiate.

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 'historical_stats_for_account'. There are no instructions on prerequisites or context, leaving the agent with no basis to choose correctly.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. However, the description adds no additional behavioral context, such as what data is aggregated, whether it includes all characters, or any 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 extremely short (two words), which is concise but at the cost of necessary information. It is not front-loaded with critical details; it merely repeats a part of the tool name.

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?

Without an output schema and with minimal parameter information, the description fails to give the agent enough context to use the tool effectively. It does not explain what 'stats' means, what the output looks like, or any 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 0%, and the description says nothing about the two required parameters (membership_type and destiny_membership_id). It does not explain their meaning, format, or how to obtain them.

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 'Account-wide stats.' is vague. It does not specify that the stats are historical, nor does it differentiate from the sibling tool 'historical_stats'. The verb is implied but not stated, and the resource scope is unclear.

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 guidelines are provided on when to use this tool versus alternatives like 'historical_stats'. There is no context about prerequisites, scoping differences, or what scenarios call for this tool.

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?

Annotations declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, but the description adds no behavioral context. It does not explain what 'cross-platform profiles' means or what actions are performed, nor does it describe side effects or permissions.

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 only two words, which is excessively brief and under-specified. It is not a model of conciseness but rather a lack of 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?

With no output schema, 3 parameters, and no parameter enums, the description must provide substantial guidance. It fails to cover the tool's purpose, behavior, or parameter usage, leaving the agent with insufficient information to use it 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 description coverage is 0%, and the description does not clarify the meaning or format of any parameter. membership_id, membership_type (number), and get_all_memberships (boolean) are left unexplained, with no enum values provided.

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?

Description 'Cross-platform profiles' is vague and lacks a verb. It doesn't specify whether the tool retrieves, searches, or updates linked profiles. Sibling tools like 'profile' and 'entity_profile' are similar, but no differentiation is provided.

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 on when to use this tool versus alternatives. No context for scenarios or prerequisites.

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds no additional behavioral context (e.g., caching, rate limits, or scope of metadata). It does not contradict annotations, but adds no value beyond them.

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 short sentence, which is concise and front-loaded. However, it could be slightly more informative without adding length.

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 0 parameters and annotations present, the description is somewhat complete for a trivial tool. However, it lacks detail on what the manifest metadata includes (e.g., structure or purpose), which could help an agent understand the output.

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 0 parameters and 100% coverage. Per calibration, 0 parameters baseline is 4. The description adds no param info, but none is needed as the tool takes no input.

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 'Destiny 2 manifest metadata' clearly identifies the tool as providing metadata for the Destiny 2 manifest. It uses a specific verb (implied retrieval) and resource, and while it doesn't explicitly differentiate from siblings, the resource is distinct among the list.

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 'entity_definition' or 'search_destiny_player'. The description lacks context on prerequisites or exclusions, leaving the agent without decision-support.

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?

The description adds value beyond annotations by stating the tool is rate-limited, free, and doesn't count against the tool-call quota. It does not contradict the annotations (readOnlyHint=false, destructiveHint=false) and provides useful 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 relatively concise at about 80 words, with key information front-loaded (purpose, when to use, rate limits). It could be slightly shorter by removing redundant phrasing, but overall it's well-structured and efficient.

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 3 parameters with full schema descriptions, no output schema, and annotations, the description adequately covers the tool's context. It explains the feedback categories, rate limits, and quota behavior, which is sufficient for a feedback tool.

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 100% description coverage for all parameters, so the description adds minimal additional semantic meaning. It mentions the types briefly but does not go beyond what the schema already provides.

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 is for telling the Pipeworx team about bugs, missing features, data gaps, or praise. It uses specific verbs (tell, is broken, missing, needs to exist) and distinguishes from sibling tools like 'ask_pipeworx' or 'discover_tools' by focusing on feedback collection.

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 explicitly explains when to use the tool with categories (bug, feature, data_gap, praise) and examples. It also mentions rate limits (5 per identifier per day) and that it's free. However, it doesn't explicitly state when not to use it or provide alternatives, though the context is clear.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral context: it describes the read-only nature (checking monotonicity) and explains the return value ('ranked opportunities with suggested trade direction + reasoning'). This enriches the agent's understanding beyond annotations.

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 detailed but well-structured with clear mode breakdowns and examples. It is front-loaded with the core purpose and modes. However, it could be slightly more concise without losing clarity.

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 absence of an output schema, the description adequately describes the return value. Both parameters are explained in context. The tool's behavior is fully described for a user to understand its capabilities and limitations.

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?

Input schema has 100% description coverage, but the description adds value by explaining the two modes and their use cases, e.g., 'event' takes a slug or URL, 'topic' takes a seed question. This clarifies the meaning beyond the schema's brief descriptions.

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: to find arbitrage opportunities on Polymarket by checking monotonicity violations. It outlines two distinct modes ('event' and 'topic'), making it easy to understand what the tool does. Among sibling tools, there is no direct equivalent, so it differentiates well.

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 guidance on when to use each mode: 'event' for a single event's child markets, 'topic' for cross-event searches. It highlights that cross-event mode catches cases missed by single-event mode. However, it does not explicitly state when not to use the tool or suggest alternatives, which would make it a 5.

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?

Annotations already indicate readOnlyHint=true and no destructiveness. The description adds valuable behavioral details: it groups by asset, fetches price history once, computes model probability, and ranks by edge magnitude. No contradiction with annotations.

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 first sentence stating purpose. It has 4-5 sentences, each contributing information. Could be slightly more concise, but 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?

Given the complex process (scan, group, fetch, compute, rank) and no output schema, the description sufficiently explains what the tool returns (top N ranked by edge magnitude with suggested trade direction). It covers the key aspects for an agent to use it 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 100%, so baseline is 3. The description adds context like default values (max 25, default 1wk, default 0.5) and clarifies that limit is for top N edges after ranking, which goes beyond the schema descriptions.

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 it scans high-volume Polymarket markets, returns those where Pipeworx data disagrees most with market price, and specifies the model (lognormal from FRED + coinpaprika). It distinguishes itself from siblings like polymarket_arbitrage by focusing on edge-based discovery.

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 clearly states the tool is built for the 'what should I bet on today' question and helps discover opportunities without manual paging. It implies usage context but does not explicitly mention when not to use or list 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?

Annotations already declare readOnlyHint and openWorldHint, but the description adds no extra behavioral context such as performance, data limits, or specific effects beyond listing components.

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 only three words, which is underspecified rather than concise; it fails to convey essential operational details.

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 tool with three required parameters and no output schema, the description is completely inadequate—it omits how to use parameters, what the response contains, and any usage 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?

With 0% schema description coverage and no parameter explanations in the description, the meaning of 'components' as a string and the required IDs remain unexplained, severely hindering correct invocation.

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 'Profile + characters + inventory' vaguely indicates it returns combined profile data, but lacks a verb and specific resource, making it unclear whether it's a retrieval or other operation.

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 on when to use this tool versus siblings like 'character' or 'entity_profile', and no mention of when not to use it.

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?

Adds scoping information (by anonymous IP, BYO key hash, or account ID) beyond the readOnlyHint and destructiveHint annotations. No contradictions.

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?

Three sentences, front-loaded with purpose, then usage, then scoping and pairing. 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?

Given one optional parameter, no output schema, and good annotations, the description covers purpose, usage, scoping, and relationships thoroughly.

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 100% and the description adds minimal value: 'omit to list all keys' is already in the schema description. Baseline 3.

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?

Clearly states it retrieves a value saved via remember or lists all keys if no key argument. Distinguishes from siblings remember and forget.

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?

Provides explicit use cases like retrieving user's target ticker, address, or research notes. Mentions pairing with remember and forget, though does not explicitly state when not to use.

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?

Discloses parallel fan-out to SEC EDGAR, GDELT, and USPTO, and return format including citation URIs. Annotations already indicate read-only and non-destructive behavior. Adds value beyond annotations but doesn't mention potential latency or data freshness 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?

Single paragraph, front-loaded with purpose, no redundant sentences. Every sentence adds value: examples, data sources, parameter details, return format.

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?

Despite no output schema, description covers return values (structured changes, count, URIs), data sources, and parameter behavior. Given tool complexity and good annotations, description is 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 coverage is 100%, so baseline is 3. Description adds concrete examples for 'since' (ISO date and relative shorthand), explains 'value' as ticker or CIK, and clarifies 'type' limitation. This enriches understanding beyond schema descriptions.

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?

Description clearly states the tool monitors recent changes for a company, using specific verbs and resources. It lists example user queries and differentiates from siblings by focusing on change detection across multiple data sources.

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?

Provides explicit use cases and example queries, making it clear when to invoke. Lacks explicit 'when not to use' or alternative tools, but the context is sufficient for agent decision-making.

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?

Discloses key behaviors beyond annotations: key-value storage, scoping by identifier, persistence (24h for anonymous, permanent for authenticated). Annotations correctly show readOnlyHint=false and destructiveHint=false, and description adds context without contradiction.

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?

Concise description (3 sentences) that front-loads the core purpose. Every sentence adds value: purpose, usage guidance, and behavioral details. 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?

Covers purpose, usage, and behavioral details for a write tool. Lacks explicit mention of what the agent receives upon success (e.g., confirmation message), but the tool is simple and the description is sufficient for understanding how to use it.

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 has 100% coverage for both parameters with descriptions. Description adds meaning by explaining the key-value pair concept, examples in schema, and scoping behavior. Slightly exceeds baseline 3 due to added context.

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?

Clearly states the tool's purpose with a specific verb ('save') and resource ('data'). Distinguishes itself from siblings like 'recall' and 'forget' by explaining the pair relationship.

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?

Explicitly describes when to use (when something worth carrying forward is discovered) and mentions alternatives ('recall' to retrieve, 'forget' to delete). Includes persistence details for different user types.

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?

Annotations already declare readOnlyHint and destructiveHint. Description adds that it returns IDs plus pipeworx:// citation URIs, offering behavioral detail beyond annotations. No contradictions.

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?

Description is concise with two sentences plus examples, front-loading the primary purpose. No unnecessary words. Could be slightly more structured but is efficient.

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 output schema, description sufficiently explains return values (IDs plus citation URIs) and provides usage context. Includes all necessary information for a lookup tool of low 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 coverage is 100% with parameter descriptions. Description adds value with examples (e.g., 'Apple' → AAPL) and explains the output, enriching semantic understanding beyond schema alone.

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?

Description clearly states it looks up canonical identifiers (CIK, ticker, RxCUI, LEI) for companies or drugs. Uses specific verbs and examples, distinguishing it from sibling tools by specifying its role as a prerequisite for other tools.

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?

Explicitly says 'Use when a user mentions a name and you need the ... IDs' and 'Use this BEFORE calling other tools that need official identifiers.' Provides clear context but does not specify when not to use or name alternatives, though no direct competitors exist among 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description does not add any behavioral details beyond what the annotations provide, such as rate limits or authentication needs.

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, concise sentence without unnecessary words. It is front-loaded with the action and resource.

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 output schema, the description should outline what the tool returns (e.g., player profile) but does not. It also lacks information on error handling or 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%. The description only hints at display_name_with_code being the primary parameter but does not explain membership_type (e.g., valid values). It minimally compensates for the lack of schema descriptions.

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 'Find' and the resource 'Destiny player', and specifies the search method 'by display name with code'. It distinguishes from the sibling tool 'search_destiny_players_by_global_name' by implying a specific identifier format.

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 given on when to use this tool versus alternatives like search_destiny_players_by_global_name. No prerequisites or context are provided.

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?

Annotations already provide readOnlyHint and openWorldHint; description adds no behavioral detail (e.g., pagination, result limits, authentication). Does not go beyond structured data.

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?

Extremely short at one sentence, but underspecified. Lacks structure: no parameter details, examples, or usage context. Not appropriately sized for a functional tool.

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?

No output schema, no details on result format, search behavior, or error handling. Incomplete for effective tool invocation despite low parameter count.

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%; description fails to explain 'page' and 'display_name_prefix' parameters. No indication of format, constraints, or expected values.

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?

Description 'Search Bungie names.' is vague; does not specify it's a global name search or differentiate from sibling tool 'search_destiny_player'. Lacks verb specificity and resource clarity.

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 on when to use this tool vs alternatives like 'search_destiny_player'. No context on typical use cases or exclusion criteria.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds no extra behavioral context. It does not mention any side effects or permissions beyond what annotations imply.

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?

Extremely short but at the expense of clarity. It lacks critical information, making it under-specified rather than efficiently concise.

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?

With two required parameters and no output schema, the description should provide context about the tool's purpose and parameter meaning. It completely fails to do so.

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?

Input schema has two parameters with no descriptions (0% coverage). The description does not explain what 'membership_id' or 'membership_type' are, how to obtain them, or their format.

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 'Bungie.net user.' is a noun phrase that vaguely hints at retrieving user data but lacks a verb or specific action. It does not differentiate from sibling tools like 'character' or 'profile.'

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 on when to use this tool versus alternatives. No context about prerequisites, typical use cases, 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?

Annotations already indicate readOnlyHint, openWorldHint, and non-destructive behavior. The description adds value by detailing the output (verdict types, extracted form, actual value with citation, percent delta) and explaining that it replaces multiple sequential calls, which helps an agent understand the tool's behavior beyond annotations.

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 paragraph but is well-structured, starting with the main purpose, then usage guidance, then scope and output details. It is concise without being overly terse, and 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 the tool has only one parameter and no output schema, the description covers the essential aspects: purpose, usage, domain limitations, and return format. It could benefit from slightly more detail on the verdict categories, but overall it is sufficiently complete for an agent to decide when to use it.

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 100% with a well-described 'claim' parameter. The description reinforces the parameter's role but does not add significant nuance beyond what the schema already provides. Thus, a 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 function: fact-check or verify a natural-language claim against authoritative sources. It also distinguishes it from sibling tools by noting it replaces multiple sequential calls, and it specifies the supported domain (company-financial claims for US public companies).

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 cues, such as 'Use when an agent needs to check whether something a user said is true' and lists example question patterns. It also clarifies the current scope (company-financial claims via SEC EDGAR + XBRL), but does not explicitly mention when not to use or alternative tools.

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