tollbooth

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

With no annotations, the description carries full burden. It states only that it 'searches' and returns certain data, but does not disclose read-only nature, rate limits, authentication requirements, or output format. This is insufficient for a search tool with no additional safety cues.

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 sentence that is efficient and to the point. It could be slightly improved by front-loading the key verb 'Search' and including more behavioral context, but it is not verbose.

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

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

Given the tool has no output schema, the description should explain what the results look like or include typical fields. It only vaguely lists 'patient outcomes, drugs, reactions'. Additionally, with many similar health-related siblings, more contextual differentiation is warranted.

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 adequately. The description adds no extra semantic meaning beyond mentioning the data source size (20M+), which does not enhance parameter understanding. Baseline 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 that the tool searches 20M+ FDA adverse drug event reports via openFDA and lists the types of data included (patient outcomes, drugs, reactions). This verb+resource combination effectively distinguishes it from siblings like drug_labels or clinical_trials.

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 over alternatives, such as drug_labels for safety info or clinical_trials for trial results. There is no mention of context, prerequisites, or 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?

With no annotations, the description implies a read-only retrieval but does not explicitly state side effects, authorization needs, or error handling. It is adequate but not thorough.

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, front-loading the key action and resource. Every word adds value with no redundancy.

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

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

For a simple one-parameter tool with no output schema, the description covers the core functionality. It could mention the output format but is still fairly 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 the parameter well. The description adds no further meaning beyond restating the profile filtering.

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 'Get' and the resource 'drop-in agent security policy templates', with a specific scope by profile. It distinguishes from siblings like check_agent_policy by focusing on templates.

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 check_agent_policy. The description does not mention prerequisites 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?

With no annotations, the description carries the burden of behavioral disclosure. It only states what the tool returns, not whether the operation is read-only, idempotent, or requires authentication. No side effects are mentioned. This is minimal transparency for a query 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, concise sentence that front-loads the purpose and includes the return value. Every word contributes meaning, no fluff.

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 3 optional parameters and no output schema, the description does not explain default behavior when no parameters are provided, nor the structure of the output. It is adequate but leaves gaps for an agent to infer.

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 each parameter has a clear description in the schema. The tool description adds no additional meaning beyond the schema, such as parameter behavior or defaults. Baseline 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?

Description explicitly states the verb 'Query', the resource 'OWASP Agentic Top 10 threat catalog', and the scope (ASI01-ASI10). It also lists the types of information returned (threats, detection hints, mitigations, detection rule IDs). This clearly differentiates it from siblings like mcp_supply_chain_iocs or check_agent_policy.

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

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

The description implies usage when OWASP top 10 threats are needed, but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. It is implied but not 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 are absent, so the description must disclose behavioral traits. It mentions return values (risk level, missing controls, advice) but does not state whether the tool is read-only, requires authentication, or has side effects. For a scoring tool, read-only nature is implied but not explicit.

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 with no wasted words. The first sentence states the primary function and key inputs, and the second summarizes return values. It is front-loaded 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?

The description explains return values (risk level, missing controls, decomposition advice), compensating for lack of output schema. However, it does not specify the format of these outputs or provide examples. Overall, it is fairly complete for a tool with well-documented input parameters.

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%, with each parameter having a clear description. The tool description adds no additional parameter details beyond the schema, so 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 purpose: 'Score an agent's lethal trifecta risk (private data + untrusted content + outbound actions).' It specifies the verb (score) and resource (agent's trifecta risk), and the unique focus on three risk factors distinguishes it from sibling 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?

The description implies usage for assessing agent risk but provides no explicit guidance on when to use versus alternatives or prerequisites. Given the unique purpose among siblings, some implicit clarity exists, but explicit usage context is missing.

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 annotations empty, the description must disclose behavioral traits. It only states the tool provides details, not whether it is read-only, requires authentication, has rate limits, or any side effects. The minimal description does not add transparency beyond the obvious.

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

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

The description is very concise (one sentence) and front-loaded. However, it sacrifices completeness for brevity. Every word earns its place, but the lack of detail makes it less valuable. For a simple tool, this is acceptable but not exemplary.

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, no annotations), the description is incomplete. It does not clarify what details are returned (e.g., name, location, timezone), whether the output is structured or free text, or any limitations. The agent lacks sufficient context to confidently use the 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?

Schema description coverage is 0%, so the description must add parameter meaning. It only restates the parameter name 'ICAO code' without explanation of format, valid values, or examples. The agent gains no additional insight beyond the schema property name.

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 retrieves airport details using an ICAO code. The verb is implied, and the resource is specific. However, it does not differentiate from sibling tools like flight_intel or weather_alerts, though the context makes it distinct enough.

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. It does not mention prerequisites, common use cases, or conditions that make it the preferred choice. The description simply states what it does, leaving the agent to infer 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?

With empty annotations, the description should disclose behavioral traits, but it only mentions output types. It omits whether the tool is read-only, requires authentication, has rate limits, or returns raw data versus processed indices.

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 sentence, making it concise and front-loaded. However, it omits necessary details, being too brief for a tool with no other documentation.

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 the presence of many sibling tools with overlapping functionality, the description does not provide sufficient context about the tool's output format or how it differs from similar tools.

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

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

Despite 0% schema description coverage, the description adds no explanation of the 'lat' and 'lon' parameters beyond implying they specify location. No information on coordinate format, valid ranges, or defaults is 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?

The description clearly lists specific data types (PM2.5, UV index, pollutants) and mentions location, making the tool's purpose evident. However, it does not differentiate from the sibling tool 'openaq_air' which likely provides similar air quality 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 like 'openaq_air' or other weather tools. The description only states what the tool returns, not the context of 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?

Annotations are empty, so the description must carry the full burden of behavioral disclosure. It mentions 'proxies' and 'velocity scoring' but does not explicitly state whether the tool is read-only, what side effects exist, or what the 'viral flag' denotes. The behavioral model remains unclear.

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 run-on sentence that crams multiple concepts without clear structure. It is not front-loaded with a core action, and every clause seems to add complexity without clarity. A more organized, concise rewrite would improve usability.

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 a complex domain (multiple data sources, scoring), the description fails to explain what the tool returns (e.g., format of momentum_score, viral flag meaning). The 2 parameters are documented, but the overall context is incomplete for an agent to confidently use the 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?

Schema description coverage is 100% and both parameters have basic descriptions (e.g., 'Topic filter e.g. Claude Code'). The main description adds some context about 'points/hr' and time windows, but does not materially enhance understanding beyond what the schema provides. Baseline 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 is a dense, jargon-filled list of sources (HN Algolia, Reddit, pypistats, etc.) and terms (velocity scoring, momentum_score, viral flag) without a clear, concise statement of what the tool does. It reads more like a feature list than a purpose description, leaving ambiguity about the primary output.

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 any of its many siblings. There is no mention of use cases, prerequisites, or alternatives, leaving the agent to guess based on the cryptic description.

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

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

With no annotations, the description must disclose behavioral traits. It only states the data source and type, omitting details like update frequency, data latency, or response format. The tool's simplicity mitigates this somewhat, but a richer description is needed for full transparency.

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

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

The description is extremely concise (6 words), with no unnecessary words. It front-loads the essential information (source and subject) in a single 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?

The description is too minimal. For a tool with no output schema, the description should explain what the forecast contains (e.g., aurora probability, location, time range). It only states the source and topic, leaving agents guessing about the output structure.

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

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

The tool has zero parameters, and the schema coverage is 100% (trivially). Per guidelines, baseline is 3 when schema coverage is high. The description adds no extra meaning beyond the schema (which is empty), so no improvement.

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 'NOAA aurora oval forecast' clearly indicates the tool provides aurora oval forecasts from NOAA. It uses a specific resource (NOAA aurora oval) and implies the action of retrieving a forecast, distinguishing it from sibling tools like 'space_weather' and 'space_weather_kp'.

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 such as 'space_weather' or 'space_weather_kp'. The description does not mention scenarios, prerequisites, or 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?

No annotations provided, and the description fails to disclose behavioral traits such as read-only nature, rate limits, authentication requirements, or data freshness. Only a brief, non-specific statement.

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

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

The description is very short (one sentence), but it sacrifices necessary detail for conciseness. It is front-loaded but not sufficiently informative.

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 one parameter, no annotations, and no output schema, the description should clarify the parameter format and the exact return values. It fails to do so, leaving agents underinformed.

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 0% description coverage for the single 'address' parameter. The description does not add any meaning or constraints (e.g., address format, case sensitivity, network type). This leaves agents to guess.

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 'Bitcoin address balance and tx history,' which indicates the tool retrieves balance and transaction history for a Bitcoin address. However, it is vague and does not specify the exact outputs or distinguish between balance and history.

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 sibling tools like crypto_price_simple or btc_mempool_fees. No context or alternatives 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?

With no annotations, the description should fully disclose behavior. It only says 'recommended fees', omitting details like which fee levels (e.g., low/medium/high), units (sat/vB), or update frequency. This is insufficient for an agent to understand what it will receive.

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 words are too sparse to convey necessary information. While concise, the description sacrifices clarity and completeness. It does not earn its place as it lacks detail.

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 or annotations, the description should be more comprehensive. It fails to explain what 'recommended fees' includes, how to interpret the return value, or any common usage patterns.

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

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

The tool has zero parameters, and schema description coverage is 100%. The description does not add parameter-specific information, but none is needed. Baseline 4 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 'Recommended Bitcoin network fees' clearly indicates the tool returns fee estimates, distinguishing it from price or balance tools. However, it lacks an explicit verb like 'get' or 'retrieve', which slightly reduces 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 versus alternatives like crypto_price_simple or btc_address_balance. No context is provided about the fee data's nature or when to prefer other 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?

No annotations exist. The description does not disclose behavioral traits such as holiday calendars, time zone handling, or boundary conditions for date ranges.

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 concise (only 4 words) but at the cost of being underspecified. Every sentence should earn its place; this one does not provide sufficient 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 no output schema, low parameter description coverage, and no annotations, the description is entirely inadequate for an agent to use the tool correctly.

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

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

Three parameters with 0% schema description coverage. The description adds no meaning beyond parameter names like 'start_date' and 'end_date'. No formats or constraints explained.

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 is 'Business days calculator.' This is vague; it doesn't specify whether it calculates difference or adds/subtracts business days, and it doesn't differentiate from other date-related 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?

No guidance on when to use this tool vs alternatives. Sibling tools include timezone_current and other time-related tools, but no comparison is 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It explains the tool checks for signals but lacks details on output format, error handling, or what happens when the site is unreachable. This is adequate but not comprehensive.

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, well-structured sentence that front-loads the verb and objects. Every word adds value, with no redundancy or unnecessary detail.

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, no annotations), the description is largely complete. It explains the purpose and usage context. A minor gap is the lack of information about the return value or output format, but overall it is sufficient.

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 only parameter 'domain' has a clear schema description. The tool description adds no extra meaning beyond what the schema already provides, so the baseline score of 3 applies given 100% 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 tool checks specific files (robots.txt, llms.txt, security.txt, agent.json) for crawl/discovery signals, with the explicit context of being used before an agent interacts with a site. This distinguishes it from sibling tools like scrape or agent_security_policies.

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 'before an agent touches a site,' indicating the appropriate time to use the tool. However, it does not mention when not to use it or name specific alternative tools, leaving room for improvement.

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 does not disclose any behavioral traits. With no annotations (no readOnlyHint, destructiveHint), it fails to indicate whether the tool is read-only, what it returns (e.g., graph format, scope), or any side effects. This leaves the agent without critical safety and behavior information.

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 (4 words) but at the expense of completeness. It is concise but under-specified, lacking essential details that an agent needs to use the tool correctly. Brevity should not come at the cost of 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 tool has 2 parameters with no schema descriptions, no output schema, and no annotations, the description is severely incomplete. It does not explain the tool's output, parameter behavior, or how it fits into a workflow. The agent cannot properly select or invoke this tool based on the description alone.

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 two parameters (paperId, direction) with 0% description coverage. The description does not add any meaning to either parameter; it does not explain what paperId represents or what values direction can take. The agent cannot infer parameter usage from the description 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?

The description 'Citation graph via Semantic Scholar' clearly states the tool provides a citation graph, using Semantic Scholar as a data source. It distinguishes itself from sibling tools like paper_details (paper metadata) and search_papers (paper search) by focusing on the citation network.

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

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

No guidance is provided on when to use this tool versus alternatives (e.g., paper_details, search_papers). The description does not mention any prerequisites, exclusions, or typical 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?

With no annotations provided, the description carries full transparency burden. It does not disclose behavioral traits like rate limits, pagination, authentication needs, or result structure. The only additional context is the source (ClinicalTrials.gov) and scale (480K+ studies), which 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, well-front-loaded sentence that conveys the core purpose and scope without extraneous words. 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 there is no output schema and no annotations, the description should compensate. It mentions searchable fields but omits details on result format (e.g., pagination, fields returned) and doesn't clarify that the tool is read-only. It is minimally adequate but has clear 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 coverage is 100%, so baseline is 3. The description adds value by specifying that 'sponsors, phases, results' can be searched via the free-text query parameter, which isn't obvious from the schema alone. This helps the agent construct effective queries beyond just trial status.

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'), the resource ('480K+ clinical studies via ClinicalTrials.gov v2'), and the searchable fields ('Status, sponsors, phases, results'). This distinguishes it from sibling tools like adverse_events or search_pubmed, leaving no ambiguity about its function.

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 lacks any guidance on when to use this tool versus alternatives such as adverse_events (for side effects) or drug_labels. No context is provided about prerequisites (e.g., no required API key) or exclusions, leaving the agent to infer usage from the name alone.

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 empty annotations, the description must disclose behavior. It only says 'scan' implying read-only, but no details on side effects, rate limits, or data freshness. No mention of output format or pagination.

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 concise (one sentence), but lacks essential details. It is not verbose, but under-specification reduces usefulness.

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 many sibling tools and no output schema, the description fails to provide enough context. No information on return values, how to interpret results, or how this scan differs from other Polymarket tools.

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 only parameter 'limit' is not explained in the description. The schema provides type and bounds, but the description adds no meaning about what limit controls (e.g., number of 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?

Description states 'Polymarket negRisk combinatorial arbitrage scan' which identifies the platform (Polymarket), a specific type (negRisk), and the action (scan for arbitrage). However, it does not differentiate from sibling tools like polymarket_event_scan or cross_platform_arb_scan, and 'negRisk' is undefined.

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 compared to alternatives such as polymarket_market_scan or cross_platform_arb_scan. The description lacks context on prerequisites or ideal 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?

With no annotations, the description must convey behavior but only says 'Search', providing no details on mutability, authentication, rate limits, or output 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 short but underspecified, lacking essential context; it is not concise but rather insufficient.

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 no output schema and minimal parameters, the description fails to provide enough context for proper invocation or expectation of results.

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 adds no meaning to the parameters 'query' or 'jurisdiction'; their purpose remains unclear.

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 a generic action ('Search company registries') but fails to specify which registries or what information is returned, making it vague among sibling search 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?

No guidance on when to use this tool versus alternatives like trademark or patent searches; no context on typical 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 are empty, so the description carries full burden. It only states the action (look up) without disclosing behavioral traits such as rate limits, authentication needs, error handling, or reversibility. It implies a read operation but no further guarantees.

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 sentence that front-loads the main action and return info. It is efficient with no redundant words, though it could be slightly expanded without harming 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?

With no output schema, the description mentions 'Parties, filings, dates' to hint at return values. However, it lacks details on error scenarios, pagination, or required authentication. Acceptable for a simple lookup but not fully 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% for the single parameter (docket_id). The description adds no additional meaning beyond 'by ID', so it meets the baseline but doesn't enrich the parameter definition (e.g., format, 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?

The description clearly states it looks up a federal court docket by ID via the CourtListener RECAP archive, and specifies the return contents (parties, filings, dates). This is a specific verb+resource combination that distinguishes it from siblings like court_opinions.

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. Given siblings include court_opinions, the lack of context on when to use this docket lookup versus opinion search is a gap.

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 are empty, so the description carries full burden. It only discloses keyless access, but lacks details on rate limits, pagination, result format, or limitations. For a search tool, more behavioral context is expected.

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

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

The description is two sentences, front-loaded with the action and resource. Every word is necessary, no fluff or repetition.

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 full schema coverage and no output schema, the description adequately states the tool's purpose and keyless nature. However, it omits output characteristics and limitations, leaving some gaps for a search 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?

Schema coverage is 100% with descriptions for each parameter. The description adds context by listing the search dimensions, but does not significantly extend the semantic meaning beyond what the schema provides. 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 verb 'Search', the resource 'US federal court opinions', and the dimensions 'by keyword, court, date'. It also mentions the underlying service (CourtListener) and the keyless access, which distinguishes it from sibling tools like 'court_docket'.

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

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

The description implies use for searching opinions, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it state when not to use it. No exclusions or comparisons are made.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It describes matching and comparing markets with fee estimates, but does not explicitly state whether the tool is read-only or if it modifies any state. While it mentions 'conservative fee estimates,' the absence of a clear read-only/mutation statement leaves ambiguity.

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?

Two sentences with zero waste. The first sentence encapsulates the core functionality, and the second adds a critical usage qualifier. All content is essential 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 tool's complexity (cross-platform arb scan with 6 parameters, no output schema), the description is lean. It does not explain return format, pagination, or error handling. For an intelligence tool, it's minimally adequate but could be more 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?

All six parameters have descriptions in the input schema (100% coverage). The description adds overall context about fee estimates and intelligence but does not provide additional per-parameter meaning beyond what the schema already offers. Baseline 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 it matches live Polymarket and Kalshi markets for a topic and compares complementary asks after fee estimates. It specifies the verb (match and compare), the resources (markets on two platforms), and distinguishes from sibling tools like polymarket_event_scan or polymarket_market_scan which focus on single platforms.

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 states 'Intelligence only; verify both rulebooks before acting,' providing clear context for when to use (intelligence gathering) and a caution against acting without verification. It implicitly suggests not using for final trading decisions but doesn't explicitly list exclusions or 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 present, so the description must fully disclose behavioral traits. It only mentions the data source (CoinGecko) but does not address rate limits, data freshness, required permissions, or whether the price is real-time vs. delayed. The agent has no warnings about potential issues.

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?

While extremely concise (one sentence), the description is under-specified. It lacks essential details about parameters and behavior, making it closer to a placeholder than a useful tool definition. Conciseness should not come at the cost of 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 simplicity of the tool (2 params, no output schema, no annotations), the description should suffice if it covered the parameters and provided basic context. However, it fails to do so, leaving the agent uncertain about how to use the tool effectively.

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% description coverage, and the description provides no explanation of the parameters ('coin', 'currency'). The agent must guess the format, allowed values, or default for 'currency'. This is a critical gap.

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 the tool retrieves cryptocurrency prices via CoinGecko. It is specific about the verb (price) and resource (cryptocurrency), but lacks details about what exactly is returned (current price, historical, etc.). However, it is distinct enough from sibling tools, none of which are cryptocurrency-related.

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 or alternatives. There are no usage conditions, prerequisites, or comparisons to similar tools. The agent is left to infer usage from the name and description alone.

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?

Description provides minimal behavioral info ('Live') but omits crucial details like read-only nature, authentication, or rate limits; annotations are empty so full burden falls on description.

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 concise at only 4 words but lacks informative content; fails to earn its place with substantive guidance.

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 2 parameters, no output schema, and no annotations, the description is woefully incomplete for an agent to understand how to use the 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?

Schema description coverage is 0%; the description does not explain what 'base' and 'target' represent (e.g., currency codes) or provide format hints.

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

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

Description 'Live currency exchange rates' identifies the resource but lacks a verb and does not distinguish from sibling tools like crypto_price_simple or economic_indicators.

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; the description does not clarify 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?

Annotations are empty, so description must disclose behavioral traits. It only says 'Search', implying read-only, but no mention of authentication needs, rate limits, or side effects. Completely opaque.

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

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

The description is very concise (one sentence). However, it is under-specified for the complexity of the tool, sacrificing completeness for brevity. Structure is front-loaded but insufficient.

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, no annotations, 3 params with 0% coverage, the description fails to provide a complete understanding. Missing information about return values, pagination, error handling, or typical usage patterns.

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 does not explain the meaning or format of the three parameters (cve_id, keyword, severity). No examples or constraints 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 states verb 'Search' and resource 'NIST NVD CVE database'. It clearly identifies what the tool does, though it doesn't differentiate from sibling tools but the domain is distinct.

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. No mention of prerequisites, 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 are empty, so the description must itself convey behavioral traits. It states the tool fingerprints for signals but does not mention whether it is read-only, any potential side effects, rate limits, or error behavior. The description is adequate but lacks depth.

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, focused sentence of 13 words. It is front-loaded with the action and resource, and every word adds value with zero repetition or waste.

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 simple parameter, no output schema, and the description covers the purpose concisely, it is mostly complete. However, it could briefly mention the nature of the output (e.g., a list of detected signals) to fully round out the 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 100% (the only parameter 'url' has a clear description). The tool description adds no additional semantic meaning beyond what the schema already provides, resulting in a baseline score of 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?

The description uses a specific verb 'Fingerprint' and clearly identifies the resource (URL) and the categories of signals detected (framework, analytics, hosting, etc.), distinguishing it from sibling tools like 'scrape' or 'enrich_lead'.

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

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

The description implies usage for website stack detection but provides no explicit guidance on when to use this tool versus alternatives, nor any when-not conditions. With many sibling tools, context about when to use detect_stack over others would be beneficial.

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

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

No annotations provided, and the description does not disclose any behavioral traits (e.g., read-only, mutation, required 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 very short (5 words) but under-informative, failing to provide necessary details despite its brevity.

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, no annotations, and an opaque parameter, the description is severely incomplete for an agent to correctly use the 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 schema has 0% description coverage for the single parameter 'query', and the description adds no meaning or usage hints for it.

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 is vague: 'CDC disease outbreak data.' It does not specify the action (e.g., search, list, retrieve) or distinguish from sibling tools like clinical_trials or drug_labels.

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, or any context for its application.

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

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

No annotations provided, and the description does not disclose behavioral traits such as read-only nature, rate limits, or authentication needs. A simple DNS lookup is likely read-only, but this is not stated.

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 sentence, concise but lacking detail. It earns its place minimally but does not provide enough context for effective tool invocation.

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 two parameters and no output schema, the description is incomplete. It does not explain output format, parameter usage, or any constraints, leaving the agent with insufficient information.

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 fails to explain the parameters 'domain' and 'type'. The description only mentions DNS resolution but adds no meaning to the input schema.

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

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

The description clearly states the tool does DNS resolution via Cloudflare DoH, which is a specific verb+resource. However, it doesn't differentiate from sibling tools like ip_geolocation or cve_search, but the purpose is unambiguous.

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 ip_geolocation or cve_search. No mention of prerequisites, contexts, or 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?

Annotations are empty, so description carries full burden. Only implies read-only via 'Search', but no mention of rate limits, authentication, data freshness, or side effects. Lacks behavioral detail.

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?

Very concise, one sentence plus a list. No wasted words, but the structure could be improved by separating content types more clearly or adding usage hints.

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?

Adequate for a simple tool with well-documented schema, but missing return value description (no output schema) and usage guidelines. Gaps in completeness for a tool with no annotations.

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

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

Schema covers both parameters with descriptions (100% coverage). The description adds no parameter-specific meaning beyond the schema; listing label content types does not clarify parameters.

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

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

Clearly states 'Search official FDA drug labels via openFDA' with specific content types (dosage, warnings, contraindications, active ingredients), distinguishing it from siblings like adverse_events and clinical_trials.

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 prerequisites or exclusions. Given related siblings (adverse_events, drug_recalls), explicit differentiation would be helpful.

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 present; description does not disclose read-only nature, authentication needs, rate limits, or pagination. Only implies a search operation via 'Search' and 'via openFDA'.

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 sentence, front-loaded with verb and resource, no unnecessary words. Highly 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?

For a search tool with no output schema and multiple related siblings, description lacks details on result handling, data freshness, or pagination. Incomplete for effective agent 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 coverage is 100% with descriptions for both parameters. Description adds example result fields but no additional parameter guidance beyond 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?

Description clearly states it searches FDA drug/device/food enforcement recalls via openFDA, mentioning specific fields (severity, classification, recalling firm). It distinguishes from siblings like product_recalls and vehicle_recalls by specifying the FDA enforcement scope.

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 product_recalls or drug_labels. Lacks explicit context for 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, the description must fully disclose behavioral traits. It only mentions the data source (World Bank API) and time series nature, but omits critical details like authentication, rate limits, destructive actions, or return format. The disclosure is minimal.

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, well-front-loaded sentence with no wasted words. It efficiently communicates the core purpose and data source.

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 annotations, the description is minimally adequate. It identifies the data types and source but lacks details on usage, return format, limitations, or how to specify parameters (e.g., indicator codes). Gaps remain for an agent to fully assess suitability.

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% with basic parameter descriptions. The tool description adds context that the parameters are for World Bank API indicators and multi-year time series, which provides some additional meaning beyond the schema, but not rich semantics.

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 provides economic indicators (GDP, CPI, unemployment, trade data) via the World Bank API and mentions multi-year time series. It is specific about the resource but does not explicitly differentiate from siblings like fred_surprises or national_debt, though those are distinct.

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 does not provide any guidance on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use, or comparisons to other economic data tools in the sibling list.

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

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

With no annotations, the description carries full burden but only states 'Search SEC EDGAR full-text filings', omitting behavioral traits like rate limits, authentication, output structure, or pagination. Minimal disclosure.

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 one sentence with no fluff, but it is too brief given the tool's complexity. Conciseness sacrifices completeness.

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, annotations, or detailed parameter documentation, the description leaves significant gaps. The agent cannot fully understand tool behavior or response format.

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

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

Schema description coverage is 0%, so the description must compensate. It vaguely associates parameters with search dimensions ('by company, form type, or ticker') but lacks formatting details or expected input formats. Insufficient for an agent.

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

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

The description clearly states the tool searches SEC EDGAR full-text filings and specifies search dimensions (company, form type, ticker). However, it does not differentiate from siblings like sec_8k_velocity or insider_trades.

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, nor any exclusions or prerequisites. The agent must infer usage from context alone.

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 are empty, so description carries transparency burden. It states it 'returns' data (read operation) but does not disclose any side effects, authorization needs, rate limits, or cost implications. Minimal but not misleading.

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?

Two concise sentences. First sentence states the action, second lists outputs and use case. No redundant information, clearly 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 no output schema, description adequately lists return fields (name, description, tech stack, etc.), covering what the agent needs to know about results. Single parameter is fully described. Complete for a simple enrichment 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?

Schema provides 100% coverage with a clear description for the single 'domain' parameter. Description adds context about expected domain types and output but does not enhance parameter understanding beyond 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?

Description explicitly states it 'enriches a company domain' and lists specific returned fields (name, description, tech stack, etc.), clearly differentiating from sibling tools like 'detect_stack' or 'extract_contacts' which might focus on subsets.

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?

Description mentions 'useful for lead scoring and prospect research', which implies context but does not explicitly compare with alternatives or state when not to use. No concrete guidance on usage boundaries.

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

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

With no annotations, the description must disclose behavior. It only mentions extraction of visible items, but no details on rate limits, side effects, output format, or handling of dynamic content.

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, only one sentence. It is front-loaded but lacks necessary usage context.

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, the description should clarify return structure. It does not specify whether results are aggregated or how errors are reported, making it incomplete for a tool with multiple extraction targets.

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 no meaning beyond the schema's description of the URL parameter.

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 extracts visible emails, phone-like strings, social links, and specific URL types from a page. It uses specific verbs and lists resource types, distinguishing it from generic scrape 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?

No guidance on when to use this tool versus alternatives like 'scrape'. The description does not include context on prerequisites or exclusions.

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

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

No annotations are present, and the description does not disclose behavioral traits such as read-only nature, required permissions, rate limits, pagination behavior, or any side effects. The tool's behavior is largely opaque.

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 sentence, but it is under-specified. While concise, it sacrifices essential information, making it insufficiently informative for an agent to use the tool correctly.

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 annotations, output schema, and any meaningful parameter documentation, the description is severely incomplete. It fails to convey return values, operational constraints, or any context beyond the data source.

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 defines two parameters ('query' and 'agency') with no descriptions (0% schema coverage). The tool description adds no meaning beyond the parameter names, leaving their formats, allowed values, and roles unclear.

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 'Federal contracts via USAspending.gov.' indicates the tool provides federal contracts data from USAspending.gov but lacks a specific verb like 'search' or 'list', making the action somewhat vague. It does distinguish from siblings like 'federal_grants' by specifying 'contracts', but clarity is limited.

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 such as 'federal_grants' or 'federal_spending'. The description does not include context about preferred scenarios, limitations, 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 are empty, so the description carries the full burden. It implies a read-only search operation but does not disclose rate limits, authentication needs, or what happens with no results. This is adequate but lacks depth.

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

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

The description is very short and efficient, with no redundant text. It is front-loaded, but could benefit from a sentence explaining parameters or output.

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 simple schema and no output schema, the description is minimally complete. It lacks details on return type or pagination, but for a basic search tool it is adequate.

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. However, the description mentions 'Agency, eligibility, deadline' which are not parameters in the schema, potentially misleading the agent about available filters.

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 the tool searches Grants.gov for open federal funding opportunities, using a specific verb and resource. It distinguishes from sibling tools like federal_spending or lobbying_records by focusing on grants, though not explicitly.

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 such as federal_spending or regulations_search. It only states what the tool does, not the context for its 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?

No annotations provided; description only says 'Search', implying read-only but not explicitly stated. No mention of side effects, destructive behavior, or required 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?

One concise sentence front-loading the purpose. No wasted words, but could benefit from structured formatting for readability.

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, minimal description. Does not explain return format, pagination, or limitations. For a search tool with 3 parameters, more detail is needed for complete 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 covers all parameters with descriptions. Description adds no extra parameter meaning beyond schema, but hints at type values (proposed rules etc.) which matches schema enums. 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?

Description clearly states verb 'Search', resource 'daily Federal Register', and scope 'proposed rules, final rules, presidential notices'. It is specific but does not distinguish from sibling tool 'regulations_search'.

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 'regulations_search' or 'court_opinions'. No exclusions or context 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?

No annotations provided, and description only mentions the API source without disclosing behavioral traits like rate limits, request costs, or side effects (e.g., read-only nature).

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 sentence is concise and front-loaded, but could benefit from structuring into purpose and parameters for 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?

Missing details on output format, pagination, and differentiation from similar tools like 'federal_grants'; incomplete for a tool with no output schema or annotations.

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

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

Schema coverage is 100%, but description introduces 'keyword' not present in schema, causing ambiguity. The parameters are listed but no additional meaning beyond schema is added.

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 verb 'Search' and resource 'federal budget' with scope and data source, but does not explicitly differentiate from sibling tools like 'federal_grants', which may overlap.

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; no context about prerequisites or typical 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?

With no annotations, the description carries full burden. It indicates a search operation, likely read-only, and mentions the atlas is 'small' and 'curated', but lacks details on side effects, permissions, or limitations.

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, well-structured sentence that immediately conveys the tool's purpose without unnecessary 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 no output schema and empty annotations, the description provides adequate domain context but omits details on result format, pagination, or scope limitations, leaving some 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 coverage is 100% with descriptions for both parameters. The description adds general context about the resource types but does not significantly extend parameter semantics beyond the schema.

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

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

The description clearly states the tool searches a curated atlas of agent-useful resources, with specific examples (APIs, tools, payment rails, etc.), distinguishing it from sibling tools that focus on specific domains.

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

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

The description implies the tool is for finding resources, but provides no explicit guidance on when to use it vs siblings or 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?

The description only mentions the data source (adsb.lol open), but fails to disclose behavioral traits such as rate limits, data freshness, return format, or any destructive actions. With no annotations, this gap leaves the agent underinformed.

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

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

The description is very concise (two sentences) and front-loaded with key information. However, the use of dashes and slashes makes it slightly less structured, and some phrases could be clarified.

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 lacks details about the output format, default behavior when no parameters are provided, and the nature of the returned 'intel'. Given no output schema, this omission hinders the agent's ability to use the tool effectively.

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 all parameters. The description adds value by specifying supported airports and aircraft types, enriching the parameter context beyond the 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?

The description clearly specifies the tool's function: tracking executive jets and military aircraft (B-52, F-35, E-3) at specific airports (TEB, VNY, DCA) with tail filtering. It distinguishes itself from sibling tools, which cover vastly different domains like weather, news, and finance.

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

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

The description implies usage for M&A and defense-related Polymarket edge, providing context. However, it does not explicitly state when to use or not use this tool compared to alternatives, though sibling tools are largely unrelated.

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

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

With no annotations, the description should fully disclose behavioral traits. It only states 'search' without mentioning rate limits, authorization requirements, or return format. For a search tool, this is insufficient.

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 sentence, making it concise. However, it is so brief that it verges on under-specification rather than efficient communication.

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 simplicity of the tool (1 parameter, no output schema), the description could still mention return values, pagination, or the type of data retrieved. It fails to provide enough context 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?

The single parameter 'query' has no description in the schema (0% coverage) and the tool description provides no explanation of its meaning or expected format. This leaves the agent without guidance on how to formulate a query.

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 specifies the verb 'search' and the resource 'openFDA food enforcement and recalls,' clearly indicating the tool's purpose. However, it does not differentiate from sibling tools like 'food_safety' or 'product_recalls', though the specific data source provides some 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 such as 'drug_recalls' or 'product_recalls'. The description lacks any 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?

No annotations are present, and the description does not disclose any behavioral traits (e.g., read-only, rate limits, pagination). The description carries full burden but offers nothing.

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 brief (4 words) but lacks substance. It is under-specified rather than concisely informative; important details are missing.

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, no parameter details, and no behavioral disclosures, the description is incomplete for a tool with one parameter and many similar siblings.

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 only parameter 'query' has 0% schema description coverage. The description does not clarify its format, purpose, or usage. The schema provides a type but no additional meaning.

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 'openFDA food enforcement' states the data source but lacks a verb indicating the tool's action (search, list, etc.). It does not distinguish from siblings like drug_recalls or food_recall_check, which also deal with food safety 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 on when to use this tool versus alternatives such as drug_labels, food_recall_check, or adverse_events. The description provides no context for 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?

Annotations are empty, so description carries full burden. It discloses no behavioral traits such as read-only, authentication needs, rate limits, or what actions the tool performs. The description is essentially a label.

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 (5 words), but it is not concise in a helpful way. It lacks front-loaded information about the tool's action and is under-specified, wasting the opportunity for 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 tool has 2 parameters, no output schema, and no annotations, the description is grossly incomplete. It fails to explain what the tool returns, how to use parameters, or any prerequisites, leaving the agent with insufficient information.

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 adds no meaning to parameters 'limit' and 'series_id'. It does not explain their purpose, format, or usage, leaving the agent without necessary 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?

The description 'FRED economic data series' is vague and lacks a specific verb or action. It does not clarify what the tool does with the data series (e.g., retrieve, list, search) and fails to distinguish it from siblings like 'fred_surprises' or 'economic_indicators'.

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. With many sibling tools in economic and financial data, the description offers no context for selection or exclusion.

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 present, the description carries the full burden. It discloses the data source (FRED), output format (CSV), rate limit (TokenBucket 2/s), and that no API key is needed. However, it does not explicitly state that the tool is read-only, nor does it describe any side effects. The mention of 'public-domain' and 'no-key' is helpful but could be more systematic.

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

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

The description is very concise, packing key information into a single line. It is front-loaded with the tool's purpose. However, the dense jargon ('delta scoring', 'inversion flag') may reduce clarity for some agents. Overall, it is efficient but sacrifices readability.

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, the description should explain the return structure. It mentions 'csv' but does not specify columns (e.g., date, spread, inversion flag, score). The term 'surprises' is undefined, and the calculation logic is only hinted at. An agent would likely find the output ambiguous without additional 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 coverage is 100% with clear parameter descriptions ('Days back, default 14' and 'Min score'). The description adds minimal extra meaning to these parameters; 'min_score' remains vague. The baseline is 3 because the schema already provides adequate documentation, but the description could clarify the scoring mechanism further.

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 mentions FRED rate surprises and specific treasury rates (DGS10, DGS2), but it is terse and uses jargon without a clear action verb. It vaguely conveys the tool's function but does not state plainly what the tool does (e.g., 'retrieve' or 'calculate'). Sibling tools like economic_indicators and treasury_dts exist, 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 is given on when to use this tool versus alternatives like economic_indicators or treasury_dts. There is no mention of prerequisites, typical scenarios, or conditions under which this tool is appropriate. The context signals show sibling tools, but the description fails to leverage them.

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

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

No annotations exist, and the description offers zero behavioral details such as side effects, permissions, or rate limits. The agent gains no insight into what happens when the tool is invoked.

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 brief but underspecified rather than concise. It fails to convey essential information, so the brevity is a liability rather than an efficiency.

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 two parameters, no output schema, and no annotations, the description is wholly inadequate. It does not compensate for the missing structural information, resulting in a tool that cannot be used reliably.

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?

Both parameters ('model' and 'query') are undocumented. With 0% schema description coverage, the description fails to clarify their meaning, acceptable values, or formatting requirements, leaving the agent to guess.

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 'Generative video model intelligence.' is vague and lacks a verb or specific action. It reads more like a category than a tool purpose, making it unclear whether the tool generates, analyzes, or retrieves video intelligence.

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. With 80+ sibling tools, the agent receives no help in distinguishing usage contexts.

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. It does not disclose if the tool is read-only, if it has side effects, rate limits, or idempotency. The phrase 'Composite geopolitical intervention signal' hints at aggregation but lacks behavioral specifics.

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 sentence that front-loads the purpose and key data sources. It is concise without redundancy, though it could benefit from structured formatting.

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 exists, so the description should clarify the return format (e.g., structure of alert_level and signals array). It lacks details on how to interpret the signal, making it incomplete for a composite tool with multiple data sources.

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 the schema already describes all parameters (region, hours_back, min_confidence, include_thermal). The description adds no extra meaning beyond the schema definitions, so baseline 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?

Description clearly states it is a 'Composite geopolitical intervention signal' with specific data sources (GDELT, BBC, AlJazeera, ADS-B mil, Polymarket) and output (alert_level + signals array). This distinguishes it from sibling tools like regulatory_pulse or attention_momentum.

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

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

The description implies usage for geopolitical monitoring but provides no explicit guidance on when to use versus siblings like attention_momentum or regulatory_pulse. No 'when not to use' or alternatives mentioned.

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

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

With empty annotations, the description must disclose behavior but fails to do so. It does not state whether the tool reads or mutates data, requires authentication, or has rate limits.

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

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

The description is extremely short (four words), but it is underspecified rather than concise. Every sentence should earn its place; here, the single sentence is insufficient.

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 one parameter, no output schema, and no annotations, the description is completely inadequate to enable correct selection and invocation.

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

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

Schema coverage is 0%, but the description does not explain the 'repo' parameter. No format, examples, or constraints are provided, leaving the agent to guess.

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 is 'GitHub repo intelligence,' which is a tautology of the tool name and provides no specific verb or resource. It does not clarify what action the tool performs on the repo.

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?

There is no guidance on when to use this tool versus alternatives such as 'github_trending' or 'cve_search.' The description does not mention context, prerequisites, or exclusions.

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

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

With no annotations, the description carries full burden. It discloses key behaviors: results are filtered by stars>20 and recent push, sorted descending, and uses the public GitHub Search API without authentication. This provides sufficient transparency for an agent to understand the tool's behavior.

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?

Two concise sentences, no filler. First sentence defines the tool's core functionality, second adds context about the API and usage scenario. Every word 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?

The description covers purpose and parameters adequately but lacks details about the output structure (e.g., what fields are returned) and whether pagination is supported. Given no output schema, more context would be beneficial.

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 parameter descriptions in the schema are already clear. The description adds minimal value beyond the schema (e.g., mentions default for limit, but schema already has min/max). Baseline 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: 'GitHub trending repos' with specific criteria (stars >20, recent push, sorted by stars desc). It also highlights the unique aspect of using the public GitHub Search API with no key required. This clearly distinguishes it from sibling 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?

The description implies usage for discovering trending repos in the dev tooling/open source space ('Momentum proxy for dev tooling / open source virality'). It does not explicitly mention when not to use or list alternatives, but given the diverse sibling tools, the context is clear enough.

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

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

With no annotations, the description carries full burden. It discloses caching (10min), data source (Algolia), and sorting method (dwell = points/(age_h+2)). However, it does not state that the operation is read-only, nor does it mention rate limits, authentication needs, or potential errors. The disclosed behaviors are helpful but not exhaustive.

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, consisting of two short sentences. It front-loads the core purpose and key technical details (Algolia tag, dwell formula, caching, sorting) with no redundant or extraneous information. Every element serves a purpose.

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 (two optional integer parameters, no output schema, no nested objects), the description provides a solid conceptual overview including data source, algorithm, caching, and sorting. It lacks explicit mention of the return format or structure, but the intended behavior is sufficiently clear for an AI agent to understand the tool's purpose.

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 both parameters (limit, min_points) described in the schema. The tool description adds no additional explanation or context about the parameters beyond what the schema already provides. 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 identifies the tool as providing Hacker News frontpage data sourced from Algolia, with a custom sorting metric (dwell). It implicitly performs a fetch/list operation, but does not include an explicit verb like 'list' or 'get'. It distinguishes from sibling tools by specifying unique data source and sorting, though not explicitly contrasting with similar 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?

The description does not provide guidance on when to use this tool versus alternatives. No context about prerequisites, complementary tools, or when not to use it is given. The user must infer usage solely from the purpose.

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 are empty, so the description must disclose behavior. It only states the tool's purpose without explaining whether it is read-only, requires authentication, or any other behavioral traits. Minimal 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?

Extremely concise with one sentence, but this brevity sacrifices essential information. The description is under-specified and does not earn its place through meaningful 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 has two parameters and no output schema, the description should clarify what data is returned and how parameters affect results. It 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 has 2 parameters (limit and ticker) with zero schema description coverage. The description adds no explanation for these parameters, leaving their purpose and valid values 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?

The description identifies the tool as providing SEC Form 4 insider transactions, which is clear but lacks specificity about scope or data source. It does not distinguish itself from sibling tools like edgar_filings.

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. Does not mention that it focuses specifically on insider trades, nor does it provide context like typical use cases or 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?

Annotations are empty, so the description carries the full burden. It does not disclose any behavioral traits such as accuracy, data source, rate limits, or whether the operation is read-only. With no annotations, this is a significant gap.

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 sentence of 5 words, which is very concise, but it is undersized and lacks necessary detail. It could be more informative without becoming verbose.

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

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

The tool is simple with one parameter and no output schema. The description does not indicate what the return value contains (e.g., city, country, coordinates). Contextual completeness is inadequate given the minimal annotations and schema coverage.

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 one parameter 'ip' with no description and 0% schema description coverage. The description adds no meaning about the parameter format (e.g., IPv4/IPv6) or constraints. It fails to compensate for the lack of schema 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 action ('Geolocate') and the resource ('IP address'), providing a specific verb+resource pair. However, it does not differentiate from sibling tools that may also involve IP or location 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 given on when to use this tool versus alternatives. The sibling list includes many location-related tools, but no criteria or exclusions are mentioned.

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

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

With empty annotations, the description must fully disclose behavioral traits, but it only states the source ('via Open Library') and basic purpose. It does not mention rate limits, authentication, what happens on invalid ISBN, or any other operational details. This is insufficient for an agent to understand the tool's behavior.

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 sentence with only 5 words, making it very concise and front-loaded. However, it may be overly terse, omitting critical details that would not significantly lengthen it. Still, it earns points for brevity and 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 tool's simplicity (one parameter, no output schema), the description should at least hint at the return format or typical metadata fields. It does not, leaving the agent to guess what 'book metadata' includes. This incompleteness hinders 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?

The input schema has 0% description coverage, so the description must add meaning to the parameter. It only mentions 'by ISBN' without specifying format (10/13-digit), validation, or expected input conventions. This fails to compensate for the schema's lack of descriptive cues.

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: retrieving book metadata by ISBN via Open Library. It uses a specific verb ('lookup') and resource ('book metadata'), and it distinguishes itself from all sibling tools (none of which deal with book lookup).

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

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

The description implies usage for ISBN-based book metadata retrieval, but it lacks explicit guidance on when to use this tool versus alternatives. Since no sibling tool provides similar functionality, the lack of differentiation is less critical, but the absence of any when/when-not guidance prevents a higher score.

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 behavioral traits are disclosed beyond the minimal description. Since annotations are empty, the description carries full burden, but it does not mention any limitations, pagination, authentication, or what constitutes a search result.

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 sentence, front-loaded with the purpose. However, it is too brief given the need for additional context; conciseness here sacrifices 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?

With no output schema, no annotations, and incomplete parameter info, the description fails to provide a complete picture. The agent cannot infer return values, filtering behavior, or how this tool fits among many legal search siblings.

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, but it does not. The 'query' and 'court' parameters are not described, leaving the agent to infer their meaning.

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: searching federal and state judges. It uses a specific verb 'search' and resource 'federal and state judges', distinguishing it from siblings like court_docket and court_opinions.

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 over alternatives (e.g., court_docket, court_opinions). There is no mention of context, prerequisites, or exclusions.

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

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

With empty annotations, the description carries full burden for behavioral disclosure. It only states 'Search' (a read operation) but does not mention side effects, authorization requirements, rate limits, or output behavior like pagination or empty results.

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 at 8 words, front-loaded with the primary action and resource. Every word is necessary and no fluff, earning 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 output schema and no explanations of combinations (AND/OR logic), defaults, or return structure, the description is inadequate for a tool with three optional parameters. It does not convey how the parameters interact or what a typical response looks like.

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 baseline is 3. The description does not add meaning beyond the schema; it merely lists general data types (lobbyists, clients, amounts) that match the parameters but offers no additional context or formatting details.

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

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

The description clearly states the tool searches FEC lobbying disclosure records, and lists the key data fields (lobbyists, clients, amounts, issues lobbied). This specificity distinguishes it from sibling tools like federal_spending and federal_grants.

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 gives no explicit guidance on when to use this tool versus alternatives, no examples, and no conditions or prerequisites. The simple verb 'search' implies a read operation, but no usage scenarios are described.

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

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

With no annotations, the description must disclose behavioral traits. It only implies a read operation but fails to mention response format, data freshness, rate limits, error handling, or any constraints. The minimal description does not add 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 overly brief at one sentence, which qualifies as under-specification rather than effective conciseness. It lacks structure and essential details, making it inadequate for tool selection and invocation.

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 many sibling tools, two required parameters, no output schema, and empty annotations, the description is severely incomplete. It fails to explain what data is returned, how to interpret results, or any constraints, leaving the agent with insufficient information.

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 adds no meaning to the two parameters (lat, lon). It does not explain expected value ranges, coordinate system (e.g., decimal degrees), or format. The description provides zero value 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 clearly states the tool provides 'Marine conditions for any ocean coordinate,' specifying a distinct resource and scope that differentiates it from sibling tools like 'tide_data' or 'weather_current_global'. However, it lacks specificity on what 'conditions' entail (e.g., wave height, wind).

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 vs alternatives. There is no mention of use cases, prerequisites, or exclusions, leaving the agent without context to select appropriately among weather and ocean-related 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, the description must fully disclose behavior. It describes a query action but omits any behavioral traits such as being read-only, response format, rate limits, or what happens when no matches are found. The claim 'virus database' implies a read, but this is not explicit.

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?

Two sentences, both front-loaded with action and context. No wasted words; the first sentence is a clear imperative, and the second is a memorable tagline.

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

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

For a simple tool with two optional parameters and no output schema, the description adequately frames the action. However, it introduces concepts like 'email IOCs' without a corresponding parameter, and does not clarify the relationship between 'MCP packages' and the parameter 'package' (npm package name).

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 baseline clarity. The description adds minimal extra semantic value, mentioning 'versions' and 'email IOCs' that are not reflected in the parameters (only 'host' and 'package'). This mismatch slightly reduces usefulness.

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 ('Query') and the resource ('known-malicious MCP packages, versions, C2 hosts, and email IOCs'), making the tool's purpose distinct among a diverse set of sibling tools. The phrase 'virus database for MCP' reinforces this 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?

The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Sibling tools like 'agent_threat_intel' could potentially overlap, but no comparison is made.

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

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

No annotations exist, so description bears full burden. Description provides no behavioral details such as whether the tool is read-only, has side effects, requires authentication, or is rate-limited.

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 brief but at the cost of necessary information. Not concise in a useful way; it is under-specified.

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 2 parameters, no output schema, and no annotations, the description is far from complete. It does not explain what the tool returns or how to interpret results.

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 add any meaning to the parameters 'task' and 'model'. It only names them without explaining acceptable values or formats.

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 'AI model recommended settings' is vague. It does not specify what kind of settings, for which AI models, or what the tool does concretely. Lacks a clear verb and resource.

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 any alternative. No context about prerequisites or when to avoid using 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?

With no annotations, the description carries the full burden. It mentions the data source (Treasury FiscalData) but omits details on data freshness, caching, or whether authentication is needed. It adequately states the scope but lacks depth on behavior.

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 succinct sentences with no filler. It front-loads the core purpose and uses efficient language, making it easy to parse quickly.

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?

While the description conveys the tool's function and data source, it does not describe the output format or structure. With no output schema, the agent lacks detail on how the data will be returned, which could lead to ambiguity in 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?

There are zero parameters, so the baseline is 4. The description adds value by explaining that the tool retrieves both total debt and debt by instrument, which helps the agent understand the output without needing 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 tool retrieves US national debt data to the penny from Treasury FiscalData, specifying both total debt and debt by instrument. It distinguishes itself from siblings like 'federal_spending' and 'economic_indicators' by focusing narrowly on debt.

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 such as 'economic_indicators' or 'fred_surprises'. The description does not mention any prerequisites or exclusions.

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

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

With empty annotations, the description carries full burden for behavioral traits. It only mentions the data source and fields, omitting critical details like rate limits, authentication needs, result limits, data freshness, or behavior when no results are found.

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, front-loaded sentence with no wasted words. It could be slightly more structured (e.g., separate purpose and result fields) but remains 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 and no annotations, the description provides only basic context. It fails to mention return format, pagination, or limitations (e.g., US-only scope). Adequate for a simple search tool but not fully 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%, with descriptions for both parameters ('Organization name' and '2-letter state code'). The description adds no additional parameter-level meaning beyond listing the data fields returned. Baseline 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 searches nonprofit IRS 990 filings via ProPublica Nonprofit Explorer and lists specific data types (revenue, expenses, exec comp). This verb+resource combination distinguishes it from sibling tools like clinical_trials or drug_labels.

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

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

The description implies usage for nonprofit financial data but provides no explicit guidance on when to use this tool versus alternatives (e.g., federal_grants) or when not to use it. No exclusions or context are mentioned.

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

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

Adds some value beyond empty annotations: mentions v3 API with v2 fallback and disclaimer hint ('For PM market disclaimers'). However, lacks details on rate limits, authentication, or data freshness guarantees.

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?

Very concise (one sentence plus fragments). Front-loaded with key info. However, phrases like 'Env / health / geo pulse' and 'For PM market disclaimers' are cryptic and may not be helpful.

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 only 2 simple parameters, no required fields, no output schema, and empty annotations, the description provides adequate high-level context but lacks usage guidance and parameter details. Could include retrieved fields (e.g., location, measurements).

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 (limit, country described). Description adds minimal parameter context: 'by city/country' hints at country filtering but does not explain limit or provide format details. 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?

Clearly identifies it's for OpenAQ air quality data, listing specific pollutants (PM2.5/PM10/NO2/O3) and filtering options (city/country). Distinguishes from unrelated sibling tools in different domains.

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

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

No explicit guidance on when to use this tool vs alternatives like weather_alerts or wildfires. Context is implied by the domain (air quality) but no when-not-to-use or alternative references.

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 are empty, so description carries full burden. It discloses caching and auto-fetch behavior. It does not mention pagination, rate limits, or return structure beyond field names. The schema provides parameter constraints, but the description adds caching detail, warranting a 3.

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 two sentences, front-loaded with key fields and caching. No extraneous words. 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?

No output schema exists, but description lists returned fields. Caching and API source are mentioned. It lacks details on return format (array of objects) and pagination, but for a simple catalog listing, it is mostly 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% for both parameters (limit, min_context). Description does not add additional meaning beyond schema. Baseline 3 is appropriate as schemas already explain parameters.

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

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

Description clearly states the tool returns the OpenRouter model catalog with specific fields (id, name, context_length, pricing, created). The purpose is distinct from all sibling tools, which are unrelated (adverse events, security, etc.). The phrase 'For model routing decisions' further clarifies use case.

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?

Description indicates usage for model routing decisions and mentions caching behavior ('Cached 1h'), which guides when to rely on freshness. However, it does not explicitly state when not to use it or compare to alternatives; sibling tools are so different that no confusion arises, so a 4 is appropriate.

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 are empty, so the description carries full burden. It does not disclose whether the tool is read-only, requires authentication, has rate limits, or any side effects. The minimal description fails to provide 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 short sentence, which is concise but underspecified. It lacks structure and does not earn its place as it provides minimal value beyond 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?

Given the complexity of order book imbalance and the lack of annotations, output schema, and parameter details, the description is severely incomplete. It does not inform users about return values, data format, or operational 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%, and the description adds no meaning to the parameters 'token_id' and 'condition_id'. Users are left to guess what these identifiers represent.

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 calculates order book imbalance for Polymarket's CLOB, providing a specific verb-resource combination. However, it does not differentiate from sibling tools like polymarket_market_scan or polymarket_event_scan, but those have distinct purposes, so clarity is good but not perfect.

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. There is no mention of context, prerequisites, or conditions under which this tool is appropriate.

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 are empty, so the description carries full burden. It mentions 'via Semantic Scholar' hinting at an external API but does not disclose behavior such as error handling, rate limits, or required permissions. The agent cannot anticipate what happens if the paperId is invalid.

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

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

The description is very short (4 words), which is concise but borderline terse. It could benefit from a sentence providing more context while remaining efficient. It does not waste words, but also does not earn its place fully.

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 (single required param, no output schema), the description is incomplete. It does not describe the output or what 'metadata' includes. The agent cannot reliably use this tool without additional information, making it below average.

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 one required parameter 'paperId' with no description. The tool description does not clarify what format or identifier is expected (e.g., Semantic Scholar ID, DOI, arXiv ID). With 0% schema description coverage, the lack of parameter guidance is a significant gap.

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 'Paper metadata via Semantic Scholar' indicates the tool retrieves metadata for a specific paper. It is clear about the resource ('paper metadata') and source ('Semantic Scholar'), and distinguishes it from sibling tools like 'search_papers' which search rather than retrieve details. However, it lacks specificity on what metadata fields are returned.

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. For example, it does not mention that this tool should be used when a known paper ID is available, or that 'search_papers' is better for discovery. The description offers no 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?

Annotations are empty, so the description carries the full burden. It does not disclose whether the operation is read-only, any rate limits, authentication needs, or other behavioral traits beyond the fact that it is a search.

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

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

The description is very concise (two sentences) and front-loaded with the core purpose. It is efficient but could slightly benefit from more detail on usage.

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

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

For a simple 2-parameter search tool with no output schema, the description is minimal. It does not mention the return format or how results are presented, and lacks integration with the sibling tool 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?

The schema already describes both parameters, but the description adds value by specifying that the query searches across titles, assignees, dates, and abstracts, giving agents richer context for parameter use.

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

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

The description clearly states it performs 'Full-text patent search via Google Patents' and specifies the fields searched (titles, assignees, dates, abstracts), providing a specific verb+resource that distinguishes it from sibling search tools like search_arxiv or search_papers.

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 usage guidance is provided; the description does not mention when to use this tool versus alternatives, nor does it offer any exclusions 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?

Without annotations, the description bears the full burden. It discloses return values (pong, server time, tool catalog) but omits potential side effects, idempotency, or rate limits. Minimal behavioral context is provided.

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, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose and key outputs.

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 (no parameters, no output schema), the description is fairly complete. However, mentioning idempotency or suggesting frequent use would improve contextual completeness for agents.

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

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

The tool has zero parameters and schema coverage is 100%. Per rubric, baseline for 0 parameters is 4. Description does not need to add parameter info.

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

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

The description clearly states the tool is a 'Health check' that returns 'pong + server time + tool catalog'. This specific verb+resource combination distinguishes it from sibling tools, which are specialized or data retrieval 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?

The description implies usage for checking server health but does not explicitly state when to use this tool versus alternatives like other monitoring tools. No exclusions or contextual guidance 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?

With no annotations provided, the description carries the full burden. It discloses the tool is read-only ('Intelligence only') and advises verification before acting, giving useful behavioral context. No contradictions 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 extremely concise: two sentences, no wasted words. It front-loads the purpose and adds a crucial usage warning in the second 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?

Given the simple parameter set (3 params, no output schema), the description covers the tool's purpose and behavioral notes. It lacks explicit output format details, but 'Intelligence only' implies a summary. Sibling tools exist but aren't contrasted.

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 baseline is 3. The description adds overall context but does not elaborate on individual parameters beyond what the schema 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 scans one live Polymarket negRisk event for fee-adjusted outcome-sum violations. It uses a specific verb and resource, but does not explicitly differentiate from its sibling 'polymarket_market_scan', though the name and context imply a 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?

The description provides usage guidelines by stating 'Intelligence only; verify CLOB depth and resolution rules before acting', indicating when not to act on the output directly. However, it does not mention alternatives or when to prefer this tool over siblings.

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