sumo-logic-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but some potential overlap exists: get_active_alerts vs list_monitors with status filters, and resolve_alert vs disable_monitor could confuse agents. Overall, the descriptions clarify the boundaries well.
Naming Consistency4/5
The naming follows a mostly consistent verb_noun pattern with list_ for collections and get_ for single items, but there are exceptions like get_active_alerts (a list) and get_search_results (retrieval). The mixed use of list_ and get_ for similar operations is a minor inconsistency.
Tool Count2/5
At 48 tools, the set is far beyond the typical range and exceeds the 25+ threshold. While the platform is broad, this many tools creates significant selection overhead for agents.
Completeness3/5
The tool set covers core workflows like search, monitors, dashboards, and collectors, but has notable gaps: no update_source or delete_source, no create/update/delete for lookup tables, field extraction rules, or many listed resources. Many resources are read-only, which limits administrative use cases.
Average 4/5 across 48 of 48 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on July 15, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the action without mentioning read-only nature, permission requirements, potential errors, or any other behavioral context. This is a significant gap for a tool with zero annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose without any filler or redundant information. It is front-loaded and every word is useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with a complete schema and output schema present, the description is minimally viable. However, the lack of behavioral transparency (e.g., read-only confirmation, alternative usage) and the absence of any usage guidance leave the description incomplete beyond the basics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage of both parameters (source_id and collector_id) with descriptions. The tool description adds no new parameter-related information, so the baseline of 3 is appropriate since the schema already documents the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a source's full configuration' uses a specific verb ('get') and resource ('source's full configuration'), making it clear this retrieves a single source's settings. It distinguishes from list_sources by implying a single source, though it doesn't explicitly contrast with get_collector or other sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_collector or list_sources. There is no mention of prerequisites, use cases, or exclusions, leaving the agent to infer usage from the name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It adds a useful 'WARNING: This action is irreversible,' which is important for a destructive operation. However, it omits other potentially relevant traits such as permission requirements, effect on dependent resources, or error behavior, so it is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences: the action and a critical warning. It is front-loaded with the primary purpose and contains no unnecessary filler, earning every character.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter delete tool, the description is minimally adequate: it states the action and the irreversible nature. However, it lacks context on usage conditions, alternative tools, or side effects, and the existence of an output schema does not relieve the need for behavioral guidance. There are clear gaps that a more complete description could fill.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a full description for the single parameter (dashboard_id: 'Dashboard ID to delete'), giving 100% schema coverage. The description adds no additional meaning or context beyond that, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete a dashboard') with a specific verb and resource, making the tool's purpose unambiguous. However, it does not distinguish itself from sibling delete tools like delete_monitor or delete_collector, so it stops short of full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It simply states the action and warns of irreversibility, which is a behavioral note rather than usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It mentions the output fields but does not disclose pagination behavior (though limit/offset are in the schema) or clarify that this is a read-only, non-destructive operation. The nature of 'list' implies safety, so the lack of explicit safety disclosure is not a contradiction, but it is a missing detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that directly states the tool's purpose. It omits irrelevant details and is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description need not explain return values. However, the lack of guidance on when to use this tool versus search_monitors is a notable gap. The description is minimally sufficient for a simple list operation but lacks broader context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters (limit and offset) are already well described by the schema. The description adds no additional meaning or context about how these parameters affect results, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (monitors) and specifies the returned fields (names, IDs, types, statuses). However, it does not explicitly distinguish this from the sibling search_monitors tool, though the word 'all' implies a broad listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 search_monitors or get_monitor. The description only states what it does, not when it should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not mention side effects, auth requirements, rate limits, or pagination behavior. It only states what is returned, which 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence with no unnecessary words. It is front-loaded with the action and resource, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple list operation with an output schema and well-documented parameters. The description captures the core purpose and return fields. It could be improved by mentioning filtering/pagination, but the schema fills that gap, so the description is adequate for the tool's low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 does not add any parameter-related context beyond the schema. The 'all' wording slightly conflicts with filter_type, but that is not a parameter semantic issue.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'collectors', specifying the returned fields (IDs, names, types, status). It distinguishes from siblings like get_collector (single collector) and list_sources (sources of a collector).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention any exclusions or contrast with sibling tools such as get_collector or list_sources. The usage is only implied by the verb 'list'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility. It discloses the immediate effect (stops evaluation/alerting) but does not mention reversibility, whether monitor configuration is retained, permission requirements, or side effects on history/alerts. This one-line description offers limited behavioral 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action phrase and contains no redundant words. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains what the tool does but not when to choose it over alternatives or what side effects occur. Because the schema covers the parameter and an output schema exists, the main gap is contextual guidance about usage and consequences, which is acceptable for a simple tool yet not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes monitor_id (with title and description), and schema coverage is 100%. The tool description adds no additional parameter semantics, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Disable a monitor') and its consequence ('to stop evaluation and alerting'), distinguishing it from enable/delete by specifying the operational effect. This gives the agent an unambiguous understanding of the tool's primary function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'to stop evaluation and alerting' implies the tool is used when monitoring should cease, but it does not explicitly contrast with delete_monitor or provide exclusions such as 'use delete_monitor to permanently remove'. The usage context is implied rather than explicit, so a score of 3 is warranted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. 'Get' implies a read-only operation, but the description doesn't explicitly state that it has no side effects, nor does it mention permissions or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action and resource. It is efficient and avoids unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and an output schema exists, the description lacks any mention of prerequisites or relationships to sibling tools, so it's not fully complete. It adequately states the purpose but leaves contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes the only parameter 'collector_id' with 100% coverage, so the baseline is 3. The description adds no additional parameter-specific details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and names the resource 'collector' with the scope 'full configuration and status', which clearly distinguishes it from siblings like list_collectors (which lists collectors) and get_source (which gets a source).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like list_collectors or get_source. It doesn't mention whether this should be called after listing collectors or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description must disclose side effects. 'Create' implies a mutation, but the description does not mention idempotency, uniqueness constraints, permissions, or failure modes. Only the return value is described, which is helpful but insufficient for full behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action, and the second sentence adds meaningful return info. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present and parameters fully described, the description is mostly complete for straightforward creation. However, it lacks any guidance on preconditions (beyond hosted collector) or error scenarios, so it falls short of fully equipping an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions, so the description adds no parameter-level meaning. Baseline of 3 applies; the description doesn't go beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Create' with resource 'HTTP source on a Hosted collector', clearly distinguishing from sibling tools like create_hosted_collector. It also mentions the return of endpoint URL, further clarifying what the tool produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Stated 'on a Hosted collector' provides context about where the source is created, implying the collector must exist and be hosted. However, no explicit when-to-use vs alternatives or exclusions are given, so it earns a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool returns monitors in a triggered state and supports filtering by severity, which adds context. However, it does not mention pagination, ordering, or other behavioral traits like rate limits or potential side effects, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and contains no filler. It efficiently states the function and the key filtering capability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter tool with an output schema, the description is complete. It covers the core purpose and filtering behavior, while the schema handles parameter details and return structure. No additional context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters are already documented. The description briefly mentions the status parameter with its allowed values, which mirrors the schema but adds no new meaning. Limit is not discussed beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get all currently active/firing alerts.' It further clarifies the output as 'monitors in a triggered state,' which distinguishes it from sibling tools like get_alert_details (single alert) or get_monitor_status (specific monitor).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. It does not mention exclusions or compare with related tools such as get_alert_details or get_monitor_status. The usage is implied by the name and description, but there is no direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It implicitly indicates a read-only operation, but it does not disclose potential pagination, rate limits, or any other behaviors beyond the literal action. However, for a simple list tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the action verb. It contains no wasted words and effectively communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with a single well-documented parameter and an output schema present, the description is sufficient. It tells the agent exactly what the tool does, and the output schema covers return value details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% because the only parameter (collector_id) has a clear description. The tool description adds no additional meaning beyond the schema, so it meets the baseline of 3 as per the rubric.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') plus the resource ('sources') and scope ('on a collector'). It is distinct from sibling tools like list_collectors or get_source, making it unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It simply states the action, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description implies a read-only operation via 'Get,' but does not disclose additional behavioral traits such as authentication requirements or potential costs. It meets the minimum for conveying safety but lacks richer context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the verb and resource, with no unnecessary words. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter get tool, this description is adequate. The output schema likely details the return structure, so the description only needs high-level scope, which it provides. A little more specificity on what 'account status' includes would push it higher.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and there is nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with a clear resource: 'account status and data ingestion information.' This distinguishes it from sibling tools like get_monitor_status and get_collector, which target different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no context on when to use this tool versus alternatives. It only states what it does, without any exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the returned data elements but does not mention read-only guarantees, permission requirements, error behavior (e.g., 404 if not found), or any side effects. The verb 'Get' implies safety, but explicit behavioral context is limited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states the purpose, the second lists the returned fields. It is front-loaded with the verb and resource, and 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter getter with an output schema, the description adequately covers what the tool does and what it returns. It lacks explicit statements about failure modes or permissions, but the output schema fills in the return structure, making the description sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes the only parameter (table_id) as 'Lookup table ID', achieving 100% coverage. The description adds no new meaning about the parameter beyond its existence, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets a lookup table's configuration and schema, and enumerates the specific returned fields (field definitions, primary keys, TTL, size limit action, parent folder ID). This distinguishes it from list_lookup_tables and other getters by specifying the exact resource and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied: use this when you need a specific table's configuration/schema, and sibling list_lookup_tables for listing. However, the description does not explicitly state when to use this over alternatives or provide exclusions or prerequisite conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It does disclose that it runs a short query and extracts sample values rather than exhaustive values, which is helpful. However, it does not explicitly state read-only behavior, potential costs, or behavior when the metric is missing, leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loaded with the main purpose. Every sentence earns its place: the first defines the outcome, the second clarifies the mechanism and the scope of values returned. No redundant phrases or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, the output schema exists, and all parameters are documented in the schema. The description adds the key behavioral context: it runs a short query and returns dimension keys plus sample values. Minor gaps remain around from_time implications and result limits, but these are partially covered by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of the parameters: metric_name has an example and description, and from_time has a default and description. The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Get metadata (dimensions and their values) for a metric.' It further explains that it runs a short query and extracts dimension keys and sample values, which clearly distinguishes this from sibling tools like query_metrics or list_metric_definitions by specifying the unique output shape.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is implied: use this when you need dimension keys and sample values for a named metric. However, it does not explicitly state when to prefer this over alternatives such as query_metrics or list_metric_definitions, nor does it mention exclusions or prerequisites, so the guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses return fields but does not mention pagination despite a token parameter, nor any authorization or rate-limit implications. This leaves behavioral aspects ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the verb+resource. The second sentence adds return fields and usage context without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
As a simple list tool with an output schema and self-describing parameters, the description covers purpose and returns. It omits pagination behavior, but the schema provides enough for an agent to infer; overall adequate though not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both limit and token described. The description adds no extra parameter semantics, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'List all lookup tables' – a specific verb and resource. It distinguishes from sibling 'get_lookup_table' which handles a single table. It also lists returned data types, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for enumerating lookup tables, and gives context that lookup tables are used for enrichment via the 'lookup' operator. However, it does not explicitly contrast with get_lookup_table or list other alternatives, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the mechanism (querying unique _contentType values) and provides examples, but it does not mention the effect of from_time, potential cost, or safety profile. It adds some context beyond the name 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short paragraphs, front-loaded with the core purpose and followed by a concise explanation. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and a simple optional parameter, the description sufficiently conveys the tool's scope and discovery mechanism. It could be slightly more explicit about when to use it, but overall it's complete for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter with 100% description coverage, so baseline is 3. The description does not mention from_time or its role, but the schema already documents it. No additional meaning added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List metric namespaces' with a specific verb+resource, and clarifies what namespaces are via examples (HostMetrics, AwsCloudWatch). This distinguishes it from sibling tools like list_metric_definitions by explaining that namespaces are based on unique _contentType values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering available metric sources, but it does not explicitly state when to use this tool versus alternatives like query_metrics or list_metric_definitions. No exclusions or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It transparently states the read-only 'List' operation and the returned fields, which implies non-destructive behavior. However, it does not mention pagination behavior or authorization requirements, which are relevant for a list operation that may return many partitions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the primary action. It contains no filler and uses exactly the necessary sentences to convey purpose, return fields, and context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple list operation, an output schema, and well-documented parameters, the description is largely complete. It even explains what partitions do, adding useful context. The only gap is that saying 'List all' may be misleading given the pagination token parameter, which the description does not mention.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters 'limit' and 'token' are already well-documented. The description adds no additional parameter semantics beyond the schema, landing at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List all index partitions.' It specifies both the verb ('List') and the resource ('index partitions'), and further clarifies what data it returns, distinguishing it from sibling tools that manage monitors, users, or dashboards.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs to view partitions, but it does not explicitly state when to use this tool over alternatives or mention exclusions. Since no other sibling tool handles partitions, the implied context is sufficient but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits on its own. It provides filter syntax examples, which helps understanding, but it does not state whether the operation is read-only, how results are ordered or paginated, or what happens on no matches. The output schema covers return structure, but not runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two brief sentences followed by examples. It is front-loaded with purpose and zero filler. Every line earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with a complete schema and an output schema, the description is sufficient. It specifies search targets and gives filter formats. It could mention edge cases like no results or case sensitivity, but these are minor gaps for a straightforward search endpoint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all three params have descriptions). The description adds filter examples, but these are already present in the schema's query parameter description, so no additional semantic value is provided beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Search') and resource ('monitors'), and specifies searchable dimensions (name, description, status filter). This distinguishes it from siblings like list_monitors (which likely lists all monitors) and get_monitor (which retrieves a specific monitor).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied through the search verb and filter examples, but no explicit guidance is given for when to prefer this tool over alternatives such as list_monitors or get_monitor. The description does not mention exclusions or complementary tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description must carry the full burden. It discloses the read-only nature ('Get') and the return structure (folder metadata plus child items with IDs/types), but does not explain whether children include nested descendants, potential errors, or permission requirements, which would be useful 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using two sentences to state the action and the return payload. It is front-loaded with the primary purpose and every sentence adds value without unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 1-parameter read tool with an output schema, the description sufficiently covers the operation and return expectations. It mentions the folder and its children, which is the core functionality, and the output schema can handle detailed return values, so no further elaboration is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% coverage with folder_id described as 'Folder ID to retrieve'. The tool description adds only the context that the folder is a content folder, but does not provide additional meaning beyond the schema, so it meets the baseline without exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Gets a content folder and its children' and specifies what is returned: folder metadata and a list of child items (searches, dashboards, sub-folders) with IDs and types. This distinguishes it from sibling tools like get_personal_folder or get_content_by_path by explicitly focusing on a folder ID and its children.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description implies it should be used when you have a folder ID and need its contents, but it does not mention when not to use it or point to other folder/dashboard retrieval tools, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds meaningful context about the 24-column grid layout, the unique 'key' mapping requirement, and the available panel types, which are important behavioral constraints beyond the basic 'create' action. It does not cover return format or permission requirements, but the presence of an output schema mitigates the return gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the primary purpose. Every sentence earns its place: the first states the action, the second explains the essential grid layout rule, and the third lists the supported panel types. No wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 9 parameters and an output schema, the description covers the main complexity (grid positioning, panel types) but does not mention default behaviors (e.g., time range default, refresh interval options) or validation rules. The presence of a complete schema and output schema fills most gaps, making this sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all nine parameters already have meaningful descriptions. The tool description reiterates the grid layout and panel types, which partially overlaps with parameters like layout_json and panels_json, but does not add substantial new semantic meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Create a new dashboard with panels, layout, and variables', which clearly specifies the verb (create), resource (dashboard), and scope (panels, layout, variables). This distinguishes it from sibling tools like update_dashboard, get_dashboard, list_dashboards, and delete_dashboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this tool is for creating a new dashboard, but it does not explicitly mention when to use it instead of alternatives (e.g., update_dashboard for modifying existing dashboards). Usage context is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains that hosted collectors are cloud-managed, which is useful behavioral context. However, it does not disclose potential side effects, permission requirements, idempotency, or error behavior, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loads the purpose in the first sentence. The second sentence adds essential context about hosted vs. installed collectors without any filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple create operation with a complete input schema and an output schema present. The description explains what a hosted collector is and when it is used. The only gap is the lack of information about permissions or response behavior, but the output schema likely covers the latter, making the description largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all four parameters. The description adds no parameter-specific details beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Create a new Hosted collector.' It clearly distinguishes this from installed collectors, and the context about HTTP sources, cloud-to-cloud integrations, and AWS polling sources further clarifies its intended use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (for hosted collectors) and explicitly states that installed collectors cannot be created via API, which is an exclusion. It does not name a direct alternative, but that is appropriate since the sibling tools do not include another create-collector option.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly discloses the irreversible nature of the action and that it also deletes associated alerts, which goes beyond the basic delete action. However, it doesn't cover permission requirements or error behavior, so it falls short of a perfect score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and immediately states the core action, followed by a crucial warning. There is no fluff or repetition; every word adds value. This is an exemplar of concise, front-loaded writing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete tool with one parameter and no annotations, the description sufficiently covers the main side effect (associated alerts) and the irreversible nature. While it doesn't address edge cases like non-existent monitors or permission requirements, the presence of an output schema and the simplicity of the operation make this adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter (monitor_id), so the schema already fully documents what the parameter means. The description adds no additional parameter-level detail, which aligns with the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Delete a monitor and all its associated alerts.' The verb 'delete' and the resource 'monitor' are specific, and the mention of associated alerts distinguishes this from sibling tools like enable/disable/get. It is immediately obvious what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (you use this to delete a monitor), but it does not explicitly state when to use it versus alternatives like disable_monitor, nor does it mention any prerequisites or exclusions. With no explicit guidance, the usage context is only inferred from the action itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It conveys the core outcome ('resumes evaluating'), but omits potential error cases, idempotency, or permission requirements. Some context is added, but key details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler words. Every word adds value, making it exceptionally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 an output schema provided, the description is sufficient to understand the basic operation. It could mention prerequisites or error handling, but given the simplicity, completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% ('Monitor ID to enable'), so the parameter is already well-documented. The tool description does not add additional parameter-level semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Enable'), the target resource ('monitor'), and the effect ('resumes evaluating'). This distinguishes it from sibling tools like disable_monitor, which is the direct opposite.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'disabled monitor' clearly implies the intended use case, but the description does not explicitly contrast this with alternatives like update_monitor or mention what happens if the monitor is already enabled. Context is clear, but exclusions are not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the read-only nature via 'get', enumerates return fields, and constrains to active alerts. It does not mention error behavior or permissions, but those are minor for a simple retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and every sentence provides useful information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 an output schema, the description is sufficient: it states the active-alert scope and lists the returned data. The relationship between monitor_id and the alert could be more explicit, but the schema clarifies it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes monitor_id as 'Monitor ID of the alerting monitor' with 100% coverage. The description adds no additional semantic detail about the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves detailed information about an active alert and lists specific content (monitor status, trigger conditions, queries, notification config, playbook). This distinctly differentiates it from related tools like get_active_alerts (listing alerts) and get_monitor_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning 'active alert' and requiring a monitor_id, but does not explicitly state when to use this tool versus alternatives or any exclusion criteria. No guidance is given for choosing between this and other alert/monitor tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It only states what is returned, but does not mention that it is read-only, any permissions required, or error handling behavior (e.g., what happens if the path doesn't exist). This is a significant gap for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences. The first sentence front-loads the purpose, the second summarizes return values, and the third gives path format. Every sentence contributes necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 1-parameter lookup tool with an output schema, the description is nearly complete: it explains the purpose, return values, and path format. However, it could benefit from explicitly stating read-only behavior or error handling, so it is not a perfect 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'path' parameter with an example, so baseline is 3. The description adds value by explicitly stating the path prefix '/Library/' and emphasizing it as a library path, which provides a useful constraint beyond the schema example.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Look up a content item by its library path.' This is a specific verb plus resource, and the mention of returning the item's ID, name, type, and parent info helps distinguish it from sibling tools like get_folder or get_dashboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating that paths start with '/Library/' and that the tool looks up by path. However, it does not explicitly mention when not to use this tool or suggest alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It implies a read-only operation via 'Get' and clarifies the return scope, but does not disclose potential side effects, permission requirements, rate limits, or performance characteristics. The output schema helps with return format, but the description adds limited additional 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action and resource, containing no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter getter with an output schema, the description covers the essential purpose and scope. It does not address usage exclusions or error scenarios, but the simple nature of the tool and the presence of structured metadata make it adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter monitor_id with a basic description. The tool description adds no extra parameter-level context, so the baseline of 3 applies because the schema already documents the parameter sufficiently.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'monitor' and explicitly states it returns 'full configuration and current status', clearly distinguishing it from sibling tools like get_monitor_status, get_monitor_history, and mutation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (retrieving configuration and status) and implicitly differentiates it from get_monitor_status, but it does not explicitly state when not to use it or name alternatives. No exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It explicitly mentions a fallback to current status if the history endpoint is unavailable, which is valuable non-obvious behavior. However, it omits details about pagination, history limits, or error handling, though the presence of an output schema mitigates some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states the purpose, and the second sentence adds behavioral nuance about the fallback. There is no redundant information or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are covered. The description covers the core purpose, time-range behavior, and fallback behavior, which is sufficient for a simple tool. It lacks details like history retention limits or timezone handling, but these are not critical for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with parameter descriptions explaining formats for from_time and to_time. The tool description adds no additional parameter semantics beyond stating that it returns events within a time range, so it does not elevate beyond the schema baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Get alert/trigger history for a monitor', which is a specific verb+resource that clearly defines the tool's function. This distinguishes it from sibling tools like get_monitor_status (current status) and get_monitor (monitor configuration), while 'Returns events within the time range' adds scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching historical alert/trigger events, but it does not explicitly state when to use this tool over alternatives like get_monitor_status or get_active_alerts. There is no direct comparison or exclusion, leaving the use case to be inferred from the name and basic description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the possible return states (Normal, Critical, Warning, MissingData, Disabled), which is useful. However, it does not mention permissions, side effects, error conditions, or whether the operation is read-only (though the name implies it). This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundant content. The first sentence states the action and resource, and the second lists the return values. Information is front-loaded and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, output schema present), the description is complete enough. It explains what the tool does and what it returns, and the output schema handles return value details. It could mention error scenarios, but that is not critical for this simple read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has full coverage (100%) for the single parameter monitor_id, including its description. The tool description does not add any information about the parameter beyond what the schema already provides, so it meets the baseline for schema-heavy coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('monitor'), clearly stating the scope as 'current health and triggering state'. This distinguishes it from siblings like get_monitor (which likely returns full configuration) and get_monitor_history (which returns historical data), so 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.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear that this tool is for checking the current health/triggering state of a monitor, providing clear context for when it should be used. However, it does not explicitly state when not to use it or point to alternatives (e.g., use get_monitor_history for historical trends), so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 return fields (budget names, scopes, capacity, timezone, etc.) which adds behavioral context, but does not mention side effects, permissions, or pagination behavior. The schema hints at pagination via the token parameter, but the description omits this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no fluff. It opens with the core action, then details return values, then provides domain context. Every sentence earns its place, making it appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the purpose, return fields, and domain context. An output schema exists, so return values are formally captured. Missing details like pagination and explicit usage prerequisites are minor gaps for a list operation, but overall it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'limit' and 'token' having clear descriptions. The tool description adds no parameter-specific information beyond pointing out the return fields. Per the rubric, with high schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all ingest budgets (v2)' with a specific verb and resource. It distinguishes itself from sibling list tools by specifying the resource type and listing the key fields returned, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that ingest budgets control data volume limits per scope, implying this tool is for reviewing those limits. It does not explicitly exclude scenarios or name alternatives, but since no other ingest budget tools exist among siblings, the usage context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the response contents (role names, capabilities, assigned users, data access filters) and notes the API version (v2). However, it does not mention pagination behavior, authentication requirements, or any potential side effects (though as a list operation, side effects are unlikely). The absence of such details leaves some gaps, but the read-only nature is implied by 'List' and the return information is sufficient for basic understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded. The purpose is stated in the first sentence, and the second sentence succinctly summarizes the return payload. There is no redundant or filler content; every word contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two optional parameters, an output schema exists), the description covers the essential aspects: what it lists, the API version, and the kind of data returned. The output schema presumably defines the exact return structure, so the description does not need to enumerate every field. However, it could mention that results are paginated (implied by the `token` parameter) or that all roles are returned regardless of user context, which slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides descriptions for both parameters (`limit` with max/min/default, `token` as a pagination token). Since schema description coverage is 100%, the description does not need to add parameter-specific details. The tool description does not elaborate on these parameters, so it stays at the baseline score of 3, relying on the schema to convey parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List all roles in the account (v2 API).' It uses a specific verb (list), identifies the resource (roles), and specifies the scope (account). It also distinguishes this tool from siblings by focusing on roles, which none of the sibling tools explicitly handle. The additional details about returned fields (role names, capabilities, assigned users, data access filters) further clarify its unique purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: to list roles and retrieve their associated details. However, it does not explicitly mention alternatives or exclusion criteria. Given that no sibling tool serves a similar role-listing function, the lack of an explicit alternative is acceptable, but it could still benefit from a phrase like 'Use this when you need role information' to fully satisfy the 'when-to-use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral detail beyond the name by explaining the pagination mechanism (use 'next' token) and specifying the response contents. With no annotations provided, this is useful disclosure for a read operation, though it stops short of discussing permissions or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no filler. The pagination instruction is efficiently integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the output schema is present, so the description need not detail return values. It explains the pagination workflow sufficiently 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions (limit and token). The description reinforces the token's role in pagination but adds little beyond the schema; it mentions the response field 'next' but that's more about the output. Baseline of 3 applies due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists dashboards with pagination and specifies the return fields (titles, IDs, descriptions). This distinguishes it from sibling tools like get_dashboard (which likely retrieves a single dashboard) and create/update/delete dashboard operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a listing use case but provides no explicit guidance on when to use it versus alternatives. No mention of using get_dashboard for a single dashboard or differences from list_monitors. Usage is implied by the verb 'list'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well by disclosing the ETag fetch, merge, and optimistic locking behavior. This goes beyond a simple 'update' statement, though it could further detail error scenarios or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose, followed by a brief, informative explanation of the mechanism. Every sentence contributes meaning without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter update tool with full schema descriptions and an output schema, the description sufficiently explains the operation's workflow. The optimistic locking context is valuable, and no additional details seem necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema descriptions already cover both parameters fully (100% coverage), including an example for fields_json. The description adds no additional parameter-specific detail beyond what the schema provides, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update a collector's configuration' with a specific verb and resource, and the read-modify-write pattern adds clarity. It distinguishes itself from siblings like create_hosted_collector, delete_collector, and get_collector.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for modifying an existing collector through the read-modify-write pattern, but it does not explicitly mention when to use it versus alternatives like create_hosted_collector for new collectors. No when-not-to-use or alternative tool names are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool creates a monitor and that simple versus complex paths exist, but it does not mention permissions, side effects, validation behavior, or failure modes. The mutation intent is clear, but additional behavioral context (e.g., prerequisite folder existence, permissions required) would be valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, and each sentence adds meaningful guidance. There is no redundant information or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 15 parameters and an output schema, and the schema descriptions cover all parameters. The description provides a high-level roadmap for simple versus complex usage, which is essential for a tool with this many parameters. It could be more explicit about prerequisites like folder ownership, but overall it is sufficiently complete given the schema and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, setting a baseline of 3. The description adds value by explaining that threshold/trigger_type are for simple monitors while triggers_json/notifications_json are for complex monitors, which is not evident from individual schema descriptions. This guidance helps the agent decide which parameter groups to use.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with "Create a new Sumo Logic monitor," a specific verb+resource that clearly states the tool's function. It also distinguishes simple versus complex monitor creation, which separates it from sibling tools like update_monitor, delete_monitor, and enable_monitor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use the simple threshold parameters versus the complex JSON parameters, which is essential for correct invocation. It lacks explicit exclusions or mention of alternative tools for creating monitors, but the context is clear enough for an agent to select this tool for creating monitors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly warns that the action is irreversible and that all sources on the collector will be deleted, which are the key side effects. It does not mention permissions, rate limits, or error handling, but the most critical behavioral traits are transparently disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences. The first sentence states the action and scope, and the second delivers a critical warning. Every word earns its place, and the information is front-loaded with the primary purpose. No filler or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete tool with one parameter and an output schema, the description covers the essential context: what is deleted, the cascade effect, and the irreversibility. It does not explain return values (handled by the output schema) or mention prerequisites like permissions, but given the tool's simplicity, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the parameter collector_id is already described as "Collector ID to delete." The description does not add direct parameter-level details (e.g., format, allowed values), but it does clarify that deleting the collector also deletes the sources attached to that collector, which indirectly adds semantic context. However, since the schema already covers the parameter, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: "Delete a collector and all its sources." This clearly states the action, the target (collector), and the scope (including sources). It distinguishes from siblings like delete_monitor and update_collector by specifying the collector-focused destructive behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (to delete a collector) and includes a warning about irreversibility and the cascade deletion of sources, which helps the agent understand the consequences. It does not explicitly name alternatives or exclusions, but the purpose is so specific that usage is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns time-series data and supports specific operators, which is useful. However, it does not explicitly state whether the operation is read-only or describe potential side effects, rate limits, or error behavior. The word 'query' implies read-only, but the absence of explicit safety context leaves some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a front-loaded purpose statement followed by two supporting sentences. Every sentence earns its place, providing syntax compatibility and operator examples without any fluff. It is easy to scan and directly actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the description covers the essential aspects: what it does, syntax compatibility, and supported operations. The input schema is detailed (100% coverage), and an output schema exists, so return formats are not needed in the description. It could mention time-range defaults or rollup behavior, but those are already in the schema, so the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explaining the query syntax and listing supported operators (avg, sum, min, max, etc.) and grouping, which goes beyond the schema's individual parameter descriptions. This helps agents construct valid queries using the 'query' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute a metrics query') and the resource ('metrics query'), and distinguishes it from sibling tools like search_logs by specifying time-series metrics data. The verb 'execute' is specific and the scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for metrics queries by stating it uses the same syntax as the Sumo Logic UI and lists supported operators. However, it does not explicitly mention when not to use it or name alternatives like search_logs or validate_query. The context is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It transparently discloses the key side effect: the monitor is disabled, not just the alert resolved. It also mentions auto-resolve behavior and the ability to reactivate with enable_monitor, giving a clear picture of the tool's impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each earning its place: the first states the action, the second provides context, and the third gives recovery guidance. No fluff, front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 an output schema, the description is nearly complete. It explains what, why, and how to reverse, but doesn't mention edge cases (e.g., alert already resolved or monitor already disabled) or explicitly compare with disable_monitor. Still, it is sufficient for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already describes monitor_id as the "Monitor ID of the alert to resolve." The description adds minimal further meaning by clarifying that the monitor itself is disabled, but this is largely implied. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action: "Resolve an active alert by disabling its monitor." It names the verb (resolve), the resource (alert), and the mechanism (disabling monitor), distinguishing it from other monitor-related tools like disable_monitor and delete_monitor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use the tool: for manual resolution when auto-resolve doesn't happen. It also names the follow-up tool (enable_monitor) for reactivation. However, it doesn't explicitly contrast with disable_monitor when you only want to disable without resolving an alert, so it's not a full 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description itself discloses that cancellation stops a running job and releases resources. However, it doesn't detail what happens if the job ID is invalid or if cancellation fails, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that is immediately comprehensible and free of redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter cancellation tool with an output schema and stable sibling context, the description covers the essential purpose and effect. No further details are needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents job_id with an explanatory description. The tool description adds no additional parameter-level detail, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Cancel') and the target resource ('a running search job'), distinguishing this tool from siblings like search_logs, get_search_status, and get_search_results. The additional clause about freeing server-side resources reinforces its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a search job is running and no longer needed. It doesn't explicitly mention alternatives or when not to use, but the context is clear within the lifecycle of search-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly discloses the return content (panels, layout, variables, time range, visual settings) and implies a read-only operation via 'Get'. It does not mention side effects or error conditions, but for a simple read tool this is adequate and adds value beyond the minimal 'Get dashboard'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, 28 words, front-loaded with the primary purpose and then supplementary detail. Absolutely no fluff or redundancy; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with one parameter and an output schema, the description is fully sufficient. It explains the scope of the returned configuration, and since an output schema exists, further elaboration on return values is unnecessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (dashboard_id is self-explanatory). The description adds no additional parameter meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Get a dashboard's full configuration' with a specific verb 'Get' and resource 'dashboard's full configuration'. It also enumerates the included elements (panels, layout, variables, time range, visual settings), distinguishing it from sibling tools like list_dashboards or delete_dashboard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating that it returns the complete configuration, implying it should be used when the full dashboard definition is needed. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous enough for an agent to infer correct usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It discloses that the tool returns the root folder including child items, which adds useful behavioral context. However, it does not explicitly state read-only semantics, authentication requirements, or potential errors, leaving some ambiguity for a getter with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, and no wasted words. Each sentence adds meaningful information: what it returns and how to use the result.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless getter with an output schema, the description is complete: it explains what the tool returns, the scope ('current user's personal'), and how to use the result. The output schema covers return structure, so no further detail is needed here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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%, so the baseline is 4. The description adds meaning by explaining the returned ID's purpose ('starting point to navigate the content library'), which helps the agent understand how to use the output even though there are no inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get the current user's personal content folder') and distinguishes this from generic folder tools like get_folder by specifying 'personal' and 'current user's'. The verb and resource are explicit and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool ('Use the returned ID as a starting point to navigate the content library'). It does not explicitly contrast with siblings like get_folder or get_content_by_path, but for a simple root-fetching tool this is sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses useful behavioral details: it returns current state, message count, record count, and warns about pending warnings/errors 'since the last status check.' This indicates statefulness and what the caller can expect, though it does not discuss side effects or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and every sentence provides value. It avoids fluff and is immediately scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a simple status check with one fully documented parameter and an output schema, the description is complete. It summarizes what the tool returns without needing to restate the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single parameter (job_id) with a clear description. The tool description adds no additional parameter-level detail, but because schema coverage is 100%, 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a clear, specific verb-resource pair: 'Check the status of a running or completed search job.' It clearly distinguishes from sibling tools like search_logs (which starts a search), get_search_results (which retrieves results), and cancel_search (which stops a job).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes when to use this tool: to check the status of a search job. It does not explicitly name alternatives or exclusions, but the context of 'running or completed search job' makes the intended use case clear relative to search-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the specific data returned and explains the role of FERs in the ingest pipeline, which adds valuable context. While it doesn't explicitly state that the operation is read-only, the 'List' verb implies it, and the background info on FERs is more than sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: the first sentence states the purpose, and the second sentence lists return fields and provides contextual background. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema and complete parameter schema, the description fully covers purpose, return contents, and contextual background about FERs. There are no significant gaps that would hinder an agent from correctly selecting and invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters (limit and token) are fully described in the input schema with types, defaults, minimums/maximums, and descriptions, achieving 100% schema coverage. The description provides no additional parameter-specific guidance, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and resource 'field extraction rules (FERs)', and clearly states what information is returned (rule names, scopes, parse expressions, enabled status, extracted field names). This distinguishes it from sibling list tools like list_fields and list_monitors, which deal with different resource types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by explaining that FERs automatically parse fields from log messages at ingest time, making it evident when this tool is useful. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It transparently reveals that the tool discovers metrics by running a short-range query, which is a meaningful implementation detail beyond the name and schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with two short paragraphs that state the purpose, mechanism, and filtering guidance without unnecessary words. Every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, has an output schema (so return format need not be explained), and the description covers the essential behavior, parameter usage, and discovery mechanism. No critical context is missing for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. The description adds semantic context for filter_query by providing examples of source category and content type, which goes beyond the schema alone, though from_time is not addressed in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List available metric names') and uniquely identifies the resource. It distinguishes from sibling 'list_metric_namespaces' by focusing on metric names rather than namespaces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a hint on how to narrow results ('Use filter_query'), but it does not explicitly explain when to choose this tool over alternatives like query_metrics or get_metric_metadata. Usage context is implied but not fully elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It clearly indicates a read operation ('List') and discloses return fields and pagination behavior via token. While it does not mention authentication or rate limits, for a simple list tool this is a reasonable level of transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with 'List all users', and contains no wasted words. It efficiently conveys purpose, return values, and pagination support.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 optional parameters) and presence of an output schema, the description is complete: it specifies scope ('all users in the account'), mentions the key return fields, and covers pagination. No additional context is needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes both parameters (limit with min/max, token with its purpose). The description's mention of 'pagination via token' aligns with the schema's existing 'Pagination token from previous response' but does not add new meaning. With 100% schema coverage, the baseline is 3, and the description adds no significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with the resource 'users' and scopes it to 'the account', which clearly distinguishes it from sibling list_* tools like list_roles and list_fields. It immediately conveys what the tool does without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (when needing to list all users in an account) and supports this with pagination details. It does not explicitly mention alternatives or exclusions, but given the sibling tools target different resources, no competing tool exists for listing users, making the usage guidance clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly explains the internal mechanism (creating a 1-second search job and immediately canceling it) and the return contract (valid=true or specific error message). This goes beyond a bare mutating/reading hint and gives the agent a realistic model of the tool's side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded. The first sentence states the purpose; the second and third explain key behaviors and output format. No filler words or redundant information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter), full schema coverage, an output schema that exists, and the description's clear explanation of input, mechanism, and return value, the tool is fully understood. No important context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single 'query' parameter with 100% coverage. The description does not add any additional parameter-level detail beyond rephrasing that a 'Sumo Logic query' is validated. This meets the baseline for good schema documentation but adds no extra semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Check if a Sumo Logic query is syntactically valid.' This unambiguously states the tool's core function and distinguishes it from any sibling tool, as there is no other validation tool in the list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool is for pre-flight validation of queries before running them. It gives clear context by explaining the minimal-job mechanism, but it does not explicitly name alternatives or when-not-to-use conditions. Still, the intended use case is unmistakable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It discloses pagination support via offset/limit and clarifies the meaning of the two result types. It does not mention potential errors or prerequisites like job completion, but the output schema covers return format. The added context about aggregated results goes beyond the raw schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the primary action. It consists of three concise sentences covering purpose, result_type guidance, and pagination. No filler or redundant content; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with a comprehensive schema (100% coverage) and an output schema, the description is largely complete. It covers the main use, the key parameter choice, and pagination. It slightly omits the prerequisite of a completed search job, but this is implied by 'from a search job' and the presence of sibling tools for status checking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics for result_type by explaining when to use 'messages' vs 'records', which is not fully captured in the schema's generic description. It also reinforces the pagination parameters (offset/limit) in context, adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch results from a search job', which distinguishes it from sibling tools like search_logs (initiating a search) and get_search_status (status checks). It also specifies the two result types (messages vs records), making the tool's scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear contextual guidance on using the result_type parameter ('Use messages for raw log lines, records for aggregated results'), which helps the agent choose the right mode. However, it does not explicitly mention when to use this tool relative to siblings (e.g., after a search job is complete) or when not to use it, though this is largely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses that a job is created, polled, results fetched, and cleanup performed—important side effects of a seemingly simple 'search'. It also informs about differing result shapes based on query type. It could add details about error handling or resource consumption, but the main behaviors are well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the main purpose front-loaded in the first sentence and lifecycle/return-type details in the second. Every sentence provides unique value; there is no redundant information or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's complexity: lifecycle handling and result variations. Since an output schema exists, exact return fields are presumably documented elsewhere. It could mention permissions or cost implications, but for a search tool this level of detail is strong and not misleading.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions, providing a baseline of 3. The description adds meaningful semantics for the query parameter by explaining that aggregation keywords (count, sum, avg, group by) change the return format, which helps users craft queries appropriately. This goes beyond the schema's basic syntax note.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a specific verb and resource: 'Execute a Sumo Logic log search and return results.' It also distinguishes itself from siblings by stating it handles the full search lifecycle (create, poll, fetch, cleanup), clearly separating it from manual management tools like get_search_status, get_search_results, and cancel_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Handles the full search lifecycle' implies this is the primary tool for running searches, versus sibling tools that handle only stages. It also provides guidance on query types by explaining that aggregation queries return aggregated records while raw queries return log messages. However, it does not explicitly name alternative tools or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains that the tool performs a read-modify-write cycle, which is a critical behavioral trait beyond a simple 'update'. It also indicates the merge semantics by instructing to pass only changed fields. However, it does not disclose error handling, idempotency, or concurrency implications, which would be extra value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise: three short sentences that lead with the core purpose, then explain the mechanism, and finish with the parameter usage. There is no redundant information; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, output schema present, no nested objects), the description is largely complete. It explains the operation, parameter semantics, and expected usage. Minor gaps include no mention of return values or error cases, but the output schema can cover return structure, and the behavior is straightforward. It is adequate for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage for both parameters, so the baseline is 3. The description adds meaningful semantic clarification by stating 'Pass a JSON object with only the fields you want to change', explicitly emphasizing partial updates beyond the schema's 'fields to update'. This helps agents understand that fields_json should not contain the full config, which is a valuable addition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update a monitor's configuration' with the verb 'update' and the resource 'monitor configuration'. It also explains the read-modify-write process, distinguishing it from simple state toggles like enable_monitor or disable_monitor. The scope is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to use the tool: 'Pass a JSON object with only the fields you want to change.' This gives practical guidance for the fields_json parameter. It does not explicitly name alternatives or exclusions, but the read-modify-write behavior and the instruction to pass only changed fields make the intended usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explicitly states that the tool tests authentication and endpoint reachability, which are the key behavioral traits. Since it is a read-only verification, no mutation implications are required. The description is transparent about what is being checked and for what purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose ('Verify that the Sumo Logic API connection is working') and then provides supporting details. Every sentence earns its place, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no parameters, no nested objects, output schema exists), the description is complete. It tells the agent exactly what the tool does and when to use it. There is no missing information that would hinder correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema confirms this. With no parameters, the baseline is 4, and the description correctly does not invent or explain parameters. It adds no unnecessary parameter information, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Verify') and resource ('Sumo Logic API connection'), clearly stating it tests authentication and endpoint reachability. It is distinct from sibling tools, which focus on monitors, logs, dashboards, etc., so there is no ambiguity about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: 'Use this to confirm credentials are configured correctly.' It does not explicitly mention alternatives or exclusions, but for a connection-check utility, this is adequate. The absence of a need for an alternative is not a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It explains that the tool returns field names, data types, and states, which is important for an agent to know. The read-only nature is implied by 'List', but it does not explicitly state that it has no side effects or mention permissions. Still, the output description adds meaningful value beyond the empty input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, with the main purpose front-loaded. It avoids redundancy and every sentence contributes useful information: the first defines the action and scope, the second explains the return value and use case. This is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and an output schema, the description is complete. It states what the tool does, what it returns, and why it is useful. The sibling-tool context and zero-parameter schema mean there are no complex gating conditions or inputs to document. The output schema handles detailed return structure, so the description's summary is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema coverage is trivially 100%. According to the rubric, a zero-parameter tool receives a baseline of 4. There is no need for parameter descriptions; the description correctly focuses on the output and purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'List all fields (built-in and custom)', which clearly identifies the operation (listing), the resource (fields), and the scope (all built-in and custom). This distinguishes it from sibling tools like list_field_extraction_rules, which focus on extraction rules rather than fields themselves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states 'Useful for understanding what fields are available for searching and building field extraction rules.' This provides a clear context for when to use the tool. It does not explicitly mention alternatives or when not to use it, but the use case is specific enough to guide selection among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly reveals the read-modify-write merge semantics, which prevents the user from expecting a full overwrite. It also warns that 'panels/layout' must be passed as complete arrays, a critical detail for correct invocation. This goes well beyond what structured fields would convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose, followed by two behavioral notes. Every sentence carries essential information with no redundancy or filler. It is concise and efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only two parameters, an output schema, and a clear behavior. The description covers the update mechanism, partial field merging, and the array requirement, leaving no ambiguity about invocation or expected behavior. The presence of an output schema means return values need not be described, so this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already explains both parameters, and the description adds value by clarifying how the fields_json parameter is used: it is merged into the existing config, not a full replacement. The warning about complete arrays for panels/layout augments the schema's example. Since coverage is 100%, a baseline of 3 applies, but the extra context earns a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Update a dashboard's configuration (read-modify-write).' The verb 'update' is specific, and 'read-modify-write' disambiguates the operation mode from simple overwrite or create. It is distinguished from siblings like delete_dashboard and create_dashboard, making the purpose explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: it explains that the tool fetches the current config, merges changes, and saves, and instructs to pass only changed fields. It does not explicitly mention when not to use it or alternatives, but the read-modify-write behavior implies the intended use case for partial updates, which is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![sumo-logic-mcp MCP server](https://glama.ai/mcp/servers/rajfirke/sumo-logic-mcp/badges/card.svg)](https://glama.ai/mcp/servers/rajfirke/sumo-logic-mcp)

Score Badge

Copy to your README.md:

[![sumo-logic-mcp MCP server](https://glama.ai/mcp/servers/rajfirke/sumo-logic-mcp/badges/score.svg)](https://glama.ai/mcp/servers/rajfirke/sumo-logic-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rajfirke/sumo-logic-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server