clockwork-mcp-remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools target a distinct Clockwork data type (queries, cache, logs, views, middleware, etc.), so an agent can generally select the right one. A few high-level analysis tools like get_performance_summary, get_timeline, explain_request_flow, and get_call_graph have overlapping purposes and could cause misselection. The two Xdebug stub tools are also nearly identical in availability, but their names make the intended difference clear.
Naming Consistency5/5
Tool names follow a very consistent verb_noun pattern, mostly built on get_, list_, search_, analyze_, detect_, compare_, and explain_. All names are snake_case and predictable. connect_clockwork is the only outlier, but it represents a distinct setup action and does not break the overall pattern.
Tool Count2/5
39 tools is excessive for an MCP server surface and exceeds the 25-tool threshold where coherence degrades. Many getters for individual request components could be grouped or parameterized (e.g., a single get_request_data tool). Each tool is individually narrow, so the set feels more like an API dump than a curated toolset.
Completeness4/5
The server covers almost every Clockwork domain: requests, queries, cache, Redis, logs, events, views, HTTP calls, queue jobs, tests, commands, auth, session, middleware, route, exceptions, and performance. The only real gaps are the two Xdebug stub tools that are explicitly unavailable, creating minor dead ends. Overall this is a near-complete read-only profiling surface.
Average 3.1/5 across 39 of 39 tools scored.
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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 of behavioral disclosure, but it only states the high-level purpose and output statistic type. It does not disclose whether authentication is required (despite username/password/token params), whether the operation is read-only, how results are structured, or any limitations such as the max 100 requests implied by the 'all' parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler and front-loads the core action. It is concise, though it trades away useful detail; still, for the dimension of conciseness and structure, it is efficient and appropriately sized for a short summary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity—11 parameters, no output schema, no annotations, and many performance-related sibling tools—the description is far too sparse to be complete. It does not explain the return format, how parameters like groupBy or since interact, authentication expectations, or what qualifies as 'route performance', leaving significant gaps for an agent selecting and invoking the 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?
Schema description coverage is 100%, so the schema already documents all 11 parameters. The description adds minimal context, such as 'percentile statistics' suggesting why count and minSamples matter, but it does not meaningfully expand on parameter semantics beyond the schema, so the baseline 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 identifies the action ('Analyze') and resource ('route performance'), and adds a specific output characteristic ('with percentile statistics') that distinguishes it somewhat from generic performance tools. However, it does not explicitly differentiate from siblings like get_performance_summary or analyze_slow_queries, so it is clear but not fully sibling-aware.
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 about when to use this tool versus alternatives such as analyze_slow_queries, get_performance_summary, or get_route_details. There are no exclusions, prerequisites, or context hints despite the large sibling list and 11 parameters, leaving the agent to infer appropriate usage.
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?
Annotations are entirely absent, so the description carries the full burden of behavioral disclosure. The one-liner only states the core filtering operation; it discloses nothing about whether the analysis is read-only, what the default threshold behavior is, how results are ordered or returned, auth requirements, or the max-100 constraint that the schema implies. It does not contradict annotations because none exist, but it leaves runtime behavior largely to inference.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clean sentence with the core purpose front-loaded and zero filler. It earns the top end of conciseness; the only slight deduction is that for an 11-parameter tool with no annotations and no output schema, the description is on the sparse side of 'appropriately sized.'
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 11 parameters, no annotations, no output schema, and roughly 35 siblings in the same domain, the description provides only the baseline function. It omits how parameter combinations interact, what the return shape looks like, how it differs from get_queries/detect_n_plus_one, and what default behavior occurs when no threshold or limit is supplied. For a tool of this complexity, the description is not complete enough for an agent to call it confidently.
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% — every one of the 11 parameters (threshold, requestId, since, uri, limit, count, baseUrl, username, password, token, all) is documented in the schema itself. Per the baseline, the description need not repeat this detail. The word 'threshold' faintly echoes the threshold parameter but adds no syntax or relationship semantics beyond the schema, so a 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 states a specific verb and resource: 'Find slow database queries above threshold.' This clearly conveys what the tool returns and the core filtering criterion. However, it does not contrast with siblings like get_queries or get_query_stats, which also concern queries, so differentiation is left to the agent.
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 given on when to use this tool versus the numerous query-related siblings (get_queries, detect_n_plus_one, get_query_stats, analyze_route_performance). There are no exclusions, no stated prerequisites such as connecting Clockwork first, and no indication of which input strategies (since vs requestId vs count) are appropriate.
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 of behavioral disclosure. It only says 'compare two requests side by side' but does not describe what the comparison output looks like, whether it is read-only, or any side effects. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no filler or redundancy. It front-loads the core action and resource, though it is arguably too terse to be fully informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is incomplete for an agent to invoke this tool confidently. It does not explain what the comparison result contains, what format it takes, or how to interpret the output. More behavioral and usage 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 description coverage is 100%, and each parameter already has a clear description such as 'First request ID' and 'Second request ID'. The tool description reinforces that the two request IDs are being compared, but it adds no extra meaning beyond the schema.
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 states a specific verb ('compare') and resource ('two requests'), which clearly distinguishes this tool from retrieval siblings like get_request or list_requests. However, it does not specify which aspects of the requests are compared, leaving some ambiguity about the exact purpose.
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?
There is no guidance on when to use this tool versus alternatives such as get_request or search_requests. The description gives no context about prerequisites (e.g., needing a connection or authentication) or situations where compare_requests is 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 the full burden of explaining behavior. 'Get high-level summary' implies a read operation, but it does not disclose what the summary contains, whether it requires authentication (though params suggest it), or what format the response takes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is concise, though slightly under-specified for a tool that needs to be differentiated from many similar sibling tools.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal: no output schema exists, no annotations are provided, and no relationship to siblings is explained. An agent could not tell what 'high-level summary' includes or how it differs from get_request or get_timeline, so the definition is incomplete for correct tool selection.
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 five parameters. The description does not add meaning beyond the schema; it only implies requestId is the focus. Baseline 3 is appropriate because the schema handles parameter documentation.
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 states a clear verb ('Get') and resource ('request'), and signals a high-level summary rather than raw data. However, it does not distinguish this from siblings like get_request or get_timeline, so it is clear but lacks sibling 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?
No guidance is provided about when to use this tool instead of get_request, get_timeline, or compare_requests. There is no mention of context, prerequisites, or exclusions, leaving the agent to guess.
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 of behavioral disclosure. It only restates the operation ('Get authenticated user') and does not mention whether credentials are required, what the response looks like, or whether any side effects occur.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is easy to parse and front-loads the main action. While brief, it avoids repetition and does not waste words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has five parameters, no annotations, and no output schema, yet the description provides almost no context beyond the tool name's meaning. It does not clarify how requestId relates to the result, how authentication is resolved, or what the response contains, leaving important gaps for 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 description coverage is 100%, so the input schema already documents all five parameters including the credential alternatives and baseUrl override. The description adds no additional parameter meaning, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific verb ('Get') and resource ('authenticated user for a request'), making the tool's core function understandable. It does not explicitly distinguish itself from sibling tools, but no sibling appears to have the same purpose.
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 gives no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or caveats. There are no explicit exclusions or references to sibling tools like get_session_data or get_request.
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 behavioral traits, and it does not. It does not mention what a cache operation is, whether results can be empty, whether authentication is required beyond the documented auth parameters, or what the response format looks like. The description merely restates the operation name and adds the request scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with zero waste—'Get cache operations for a request.' No extraneous detail or repetition. It is concise, though the substance is thin enough that the conciseness partly reflects under-specification rather than efficient authoring.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no annotations and no output schema, so the description must compensate, and it does not. An agent cannot determine what a cache operation is, what the response contains, or when to prefer this over the closely related get_cache_stats. The schema documents parameters well, but the overall tool context is materially incomplete for reliable selection among 37 siblings.
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 5 parameters (token, baseUrl, password, username, requestId) are already documented in the schema. The description adds only 'for a request,' which loosely maps to the required requestId parameter but no additional semantic value. Baseline 3 is appropriate since the schema does the heavy lifting.
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 states a specific verb (Get), resource (cache operations), and scope (for a request), which is clear enough to distinguish from siblings like get_cache_stats (aggregate statistics) and get_request (the request payload itself). However, 'cache operations' is never defined, so an agent must infer what this return shape includes. It is a clear statement but relies somewhat on the tool name for meaning.
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 about when to use this tool versus alternatives. With 37 sibling tools including get_cache_stats, get_queries, and get_request, an agent is given no criteria for selecting this tool for per-request cache activity versus the statistical view provided by get_cache_stats. There are no exclusions, prerequisites, or alternative routing cues.
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 the full burden of behavioral disclosure. It only mentions the returned data (hit ratio, totals) and says nothing about authentication requirements, time-range scoping, side effects, or whether it is a read-only operation. The presence of auth-related parameters is not reflected in the description.
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?
One short sentence with no fluff. The key action and output hint are front-loaded. Every word earns its place; the parenthetical is a useful detail without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, no annotations, and seven parameters, but the description only says 'Get cache statistics (hit ratio, totals)'. It omits important context such as whether from/to define a time range, what 'totals' refers to, and whether authentication is required. An agent can infer a basic call but not confidently understand scope or prerequisites.
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 baseline is 3. The description does not add any parameter-specific meaning beyond the schema, but it does not need to since the schema fully documents all seven parameters. No additional compensation is required.
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 names a specific verb and resource: 'Get cache statistics' and adds clarifying details '(hit ratio, totals)'. This clearly distinguishes it from related tools like get_cache_operations by focusing on aggregate stats, though it does not explicitly differentiate itself from siblings.
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 gives no guidance on when to use this tool versus alternatives such as get_cache_operations or get_redis_commands. It states what the tool does but not the conditions or scenarios that would make it the right choice.
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 of disclosing behavioral traits. It only states what the tool produces, not whether it is read-only, what input it requires beyond requestId, how minDuration affects results, whether events must exist, or any failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise, front-loaded sentence with no filler words. It communicates the essential action and output clearly, though it may be too terse to fully support tool selection.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with six parameters, no annotations, no output schema, and many siblings, a single sentence is insufficient. It does not explain the relationship between the requestId and the generated tree, the meaning of minDuration in this context, what the resulting tree looks like, or when an agent should prefer this over related tools.
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 schema already documents all six parameters. The description adds minimal extra meaning beyond indicating that timeline events are the data source, which is a useful hint but not substantial. Baseline 3 is appropriate given the high schema coverage.
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 uses a specific verb ('build') and a specific resource ('hierarchical execution tree from timeline events'), which clearly conveys the tool's core function. It does not explicitly differentiate from siblings like get_timeline or explain_request_flow, but the resource concept is distinct enough to be understood.
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 gives no guidance on when to use this tool versus alternatives such as get_timeline, explain_request_flow, or get_query_stack_trace. There is no mention of prerequisites, typical use cases, or situations where a sibling tool would be more appropriate.
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 exist, so the description carries the full burden. 'Check' weakly implies a read-only operation, but it does not disclose authentication behavior, whether a connection is required, or what kind of statistics are returned. More behavioral context would be needed for safe and correct use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff or redundancy. It is front-loaded with the verb and resource, though it is brief enough that it sacrifices potentially useful behavioral details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four authentication-related parameters, no output schema, and no annotations, yet the description only provides a high-level summary. It does not explain what the status/stats output looks like, how authentication is handled, or how this tool relates to connect_clockwork and the other status/stats siblings. This is incomplete guidance for an agent invoking it 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?
The input schema has 100% description coverage for all four parameters, so the baseline is 3. The description does not add meaningful parameter semantics beyond naming the tool's subject area, but it does not need to compensate because the schema already documents each parameter.
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 uses a specific verb ('Check') and a resource ('Clockwork storage') with a clear object ('status and statistics'). It is mostly unambiguous, though it does not explicitly differentiate itself from sibling stats tools like get_cache_stats or get_query_stats.
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 given for when to use this tool versus any of the many sibling tools. There is no mention of prerequisites such as an active Clockwork connection or whether connect_clockwork should be called first.
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 must carry the full behavioral disclosure burden. Beyond the word 'Get', it does not state what 'full details' contains, what response format to expect, whether authentication is required, or any side effects. This is too thin 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler and is front-loaded with the action 'Get full details'. It is concise, though the brevity comes at the cost of important contextual information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, five parameters, and a large sibling list, the one-sentence description is insufficient. It does not explain what 'full details' means, how requestId is used, or how this tool relates to list_commands and other request-focused siblings.
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 with descriptions, so the baseline is 3. The description itself adds little parameter meaning, but it does contextually link the tool to command execution, which helps clarify the role of requestId.
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 uses a specific verb 'Get' and names the resource 'full details of an Artisan command execution', making the basic purpose clear. It does not explicitly differentiate from siblings like get_request or list_commands, but the Artisan command focus provides reasonable distinction.
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 gives no guidance on when to use this tool versus alternatives. With many siblings such as list_commands, get_request, and search_requests, there are no conditions, prerequisites, or exclusions to help an agent choose correctly.
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 of behavioral disclosure. It only states that events are retrieved; it does not explain authentication requirements, what 'dispatched events' means, whether the operation is read-only, or what the response contains. This is minimal and leaves important behavior unknown.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler or redundant content. It is concise and every word contributes, though it is so brief that it sacrifices useful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with five parameters, no annotations, no output schema, and a large sibling set, this description is incomplete. It does not clarify what 'dispatched events' are, when to choose this tool, or how it relates to similar request-scoped tools, making it hard for an agent to invoke confidently in ambiguous situations.
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 each parameter already documented (e.g., requestId as 'Clockwork request ID' and auth parameters clearly labeled). The description itself adds no parameter-level meaning beyond what the schema provides, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get dispatched events for a request' clearly identifies a getter operation scoped to a specific request and names the resource type ('dispatched events'). It is distinct from many siblings at a high level, but it does not explicitly differentiate itself from related tools such as get_timeline or get_http_requests.
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. With 37 sibling tools, including other request-scoped getters like get_request and get_timeline, the absence of any usage direction or exclusions leaves an agent to guess which tool is appropriate.
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 behavioral disclosure, but it is a single clause stating only the operation. It does not disclose what happens when no requests exist, whether authentication must be established first, what ordering defines 'most recent', or whether the result is a single object. The auth parameters in the schema hint at prerequisites, but the description itself reveals nothing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Six words, one sentence, front-loaded with the verb and resource. There is zero redundant text or repetition of the tool name. It earns a 4 rather than 5 because the brevity edges toward under-specification rather than deliberate, complete economy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool sitting among 37 siblings — including get_request, list_requests, and search_requests — and with no output schema or annotations, this description is insufficient. An agent cannot determine the return shape, the ordering semantics, or edge-case behavior, making confident invocation uncertain. A tool this simple still needs at least a sentence about what 'latest' means and what to expect back.
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%: token, baseUrl, password, and username all have individual descriptions in the schema. Per the baseline rule for high coverage, a 3 is appropriate even though the description adds no parameter-specific meaning. The description's job here is minimal, and the schema carries the parameter documentation adequately.
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 the most recent Clockwork request' uses a specific verb (get) and resource (most recent Clockwork request). The qualifier 'most recent' does distinguish it from get_request (specific ID) and list_requests/search_requests (collections), though it doesn't explicitly name those alternatives. Slight deduction because the criterion for 'most recent' is left ambiguous.
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 about when to use this tool versus get_request, list_requests, or search_requests. There is no mention that this is the choice when you want the latest request without knowing its ID, and no exclusions or alternative conditions. Usage context is only inferable from the name, not stated.
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 must carry the full burden of behavioral disclosure. 'Get log entries for a request' indicates a read operation but provides no context on authentication, error handling, log format, or filtering semantics. The level parameter implies filtering, but the description does not explain its effect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no redundancy. It is appropriately concise, though it carries minimal information; nothing in it is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, no output schema, and no annotations, this description is insufficient. It omits when-to-use guidance, return format, auth requirements, and differentiation from the many log-related siblings such as get_log_stack_trace.
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 are already documented. The description adds no additional meaning beyond what the schema provides, such as the purpose of the level filter or the token/password authentication alternatives.
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 states a clear verb ('get') and resource ('log entries for a request'), which distinguishes it from siblings like list_requests or get_request. It is terse but not ambiguous.
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 given for when to use this tool versus alternatives like get_log_stack_trace or get_request. The description does not mention prerequisites, such as an active Clockwork connection, nor does it direct the agent to a more specific sibling.
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 full responsibility for behavioral disclosure. It conveys only that the tool retrieves something, without explaining what source location means, whether it returns a stack trace, how authentication is handled, or what errors may occur.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. It is appropriately concise, though it lacks enough detail to be considered exemplary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description provides insufficient context for an agent to fully understand the return value or behavior. It does not mention what the source location looks like, how it relates to logIndex, or what preconditions apply.
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 schema already documents all six parameters including requestId and logIndex. The description adds no parameter-level meaning beyond what the schema provides, which fits the baseline of 3.
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 a specific operation and resource: obtain the source location for a log entry. However, it does not distinguish itself from sibling tools such as get_query_stack_trace or get_logs, 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 gives no guidance on when to use this tool over alternatives. It does not mention that requestId and logIndex are needed to target a specific log entry, nor does it explain when a stack trace is available.
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 the full burden of behavioral disclosure. The verb 'Get' implies a read-only operation, but the description does not disclose authentication requirements, error behavior, output format, or any prerequisites. This is a significant gap for a bearer of authentication-related parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words and the core action is front-loaded. However, the extreme brevity also contributes to under-specification, so it is concise but not richly informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, yet the description does not explain what the middleware chain contains, what the response looks like, or how authorization and baseUrl interact. An agent would need to infer critical context from sibling tool names and parameter names alone, which is insufficient.
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 five parameters. The description adds no additional parameter semantics, which lands at the baseline for full schema coverage.
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 a specific action ('Get'), a specific resource ('middleware chain'), and a target scope ('for a request'). It is distinguishable from most sibling tools by its unique resource, though it does not explicitly differentiate itself from related request-level getters.
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?
There is no guidance on when to use this tool versus alternatives like get_request, explain_request_flow, or get_timeline. It also does not mention that a requestId must already exist or how to obtain it, leaving usage context entirely to inference.
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 present, so the description carries the full burden of disclosing behavior. It only says 'Get', which weakly implies a read-only operation, but does not state what the overview contains, whether authentication is required, what happens without the optional params, or what response to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with no wasted words. The brevity helps, though it achieves conciseness by sacrificing almost all behavioral and usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, 0 required, no annotations, no output schema, and 38 siblings, the single-sentence description is insufficient for an agent to confidently select and invoke this tool. The schema covers parameter syntax, but the agent is left guessing about request identification, auth requirements, and how this summary differs from other performance tools.
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 schema already documents all seven parameters. The description adds little beyond the phrase 'for a request', which hints that requestId is central, but it doesn't clarify the relationship between requestId and the to/from range 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 uses a specific verb ('Get'), a concrete resource ('performance overview'), and scopes it to 'a request', which helps distinguish it from broader tools like list_requests or get_timeline. It doesn't, however, explicitly name what makes this different from related siblings such as analyze_route_performance or get_query_stats.
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?
There is no guidance on when to use this tool versus the many related request/performance siblings. Nothing states what problem it solves, what triggers its use, or which alternative should be chosen for other analysis needs.
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 the full burden of behavioral disclosure, but it only states the basic operation. It does not mention authentication requirements, the meaning of the slow/threshold parameters, what the returned query list contains, or any pagination/ordering behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no fluff or repetition. It is front-loaded and concise, though it achieves conciseness by omitting useful context that other dimensions penalize.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has seven parameters, including auth-related ones, and no output schema or annotations, yet the description provides only a one-line summary. It does not explain the auth flow, the slow-query filtering semantics, or what a caller should expect in the response, leaving an agent under-equipped to invoke it 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 description coverage is 100%, so the input schema already documents all seven parameters. The description adds little beyond implying that requestId is central, which is appropriate given the schema already carries the parameter-level detail.
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 names a specific verb ('Get') and resource ('database queries') scoped to 'a request', which makes the tool's core function clear. It is distinguishable from siblings like get_query_stats and analyze_slow_queries, though it does not explicitly contrast itself with them.
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 gives no guidance on when to use this tool versus alternatives such as get_query_stats, analyze_slow_queries, or get_request. It only implies use for queries tied to a request via the phrase 'for a request', but provides no exclusions or routing cues.
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 the full burden of disclosing behavior, but it only restates the result ('source location') and does not explain what the returned location looks like, whether authentication is required, or what happens if the queryIndex or requestId is invalid. The read-only nature is implied, not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler or redundancy. It is front-loaded with the action and target, and every word contributes to the meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 6 parameters including auth fields, the description omits essential context: how requestId/queryIndex are obtained, what authentication approach is expected, and what the returned source location will contain. The tool is not fully invocable based on the description alone.
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 documents all 6 parameters with 100% coverage, so the baseline is 3. The description adds no parameter-level meaning beyond the schema's definitions for requestId and queryIndex.
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 names a specific verb ('Get') and a concrete resource ('source location for a database query'), which is clear and distinguishable from sibling tools like get_queries or get_log_stack_trace. However, it does not explicitly contrast itself with a sibling, so it stops short of full distinctiveness.
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?
There is no guidance about when to use this tool, what prerequisites exist (e.g., needing a requestId from get_queries or an active Clockwork connection), or when a sibling tool would be more appropriate. The single sentence implies a use case but does not instruct an agent on selection.
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 behavioral disclosure. It only states 'Get aggregate query statistics' without mentioning authentication requirements, the distinction between requestId-specific and aggregate results, time-range behavior, or the output format. It is not misleading, but it is far too thin for a tool with 7 parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff. It is front-loaded with the key action and resource, though it sacrifices useful detail for brevity. Structure is clean and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 optional parameters, no annotations, no output schema, and many closely related sibling tools, the description is incomplete. It omits when requestId should be used, whether the result is per-request or cross-request aggregate, and any authentication context. The schema covers parameter definitions, but the description fails to provide the needed operational 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 baseline is 3. The description itself adds no parameter meaning beyond what the schema already provides, but the strong schema descriptions cover the semantics of from/to, authentication, baseUrl, and requestId.
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 names a specific verb ('Get'), resource ('aggregate query statistics'), and scope ('for a request'), which distinguishes its basic purpose from sibling tools like get_queries or analyze_slow_queries. However, it does not explicitly differentiate from siblings or clarify the 'aggregate vs. specific request' semantics.
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 such as get_queries, analyze_slow_queries, or get_query_stack_trace. The phrase 'aggregate query statistics' implies a use case, but there is no explicit context, exclusions, or alternative routing.
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 bears the full burden of behavioral disclosure. It states only the action — nothing about what the returned data looks like, ordering, pagination, error behavior, or that authentication (via the token/password parameters in the schema) is required. For an unannotated tool this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single six-word sentence with zero filler, and the action verb is front-loaded. It is efficient, though the brevity is partly a product of under-specification rather than tight editing of rich material, so it stops short of a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and five parameters including auth-related ones, the description carries a heavy completeness burden that it doesn't meet. It fails to explain what Redis commands the agent will receive, whether they represent executed operations during the request, or how this tool differs from the nearby cache and query tools. An agent cannot confidently anticipate the tool's result or choose it 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 description coverage is 100%, so the baseline of 3 applies even though the description adds no parameter detail. The phrase 'for a request' loosely maps to the required requestId parameter, but the description contributes no meaning beyond what the schema already documents for the auth-related parameters. The baseline 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?
Names a specific verb (Get), resource (Redis commands), and scope (for a request), so the core action is clear. However, 'Redis commands' is ambiguous — it doesn't clarify whether these are executed Redis operations recorded during the request, and it doesn't distinguish itself from siblings like get_cache_operations or get_queries. This is clear but lacks sibling differentiation, matching a 4.
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. It doesn't name sibling tools like get_cache_operations or list_commands, state exclusions, or describe the conditions under which Redis commands would be relevant for a request. There is no usable routing information, leaving the agent to guess.
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 of behavioral disclosure. It only says 'Get route details', which implies a read operation, but it does not disclose authentication behavior, return format, or what data constitutes 'route details'. Nothing contradicts the schema, but the behavior is under-specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence: 'Get route details for a request'. It is front-loaded and wastes no words. However, its brevity comes at the cost of missing useful context, so it is concise but not rich.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, no annotations, and 38 sibling tools, the description is insufficiently complete. It doesn't explain what route details are needed for, how authentication parameters relate, or what response to expect. An agent would have to infer most context from the parameter names and sibling tool names.
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 100% parameter coverage, with each parameter including its own description. The tool description adds no extra meaning beyond the schema. The baseline of 3 applies because the schema already handles parameter documentation adequately.
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 states a clear verb ('Get') and a specific resource ('route details') tied to a request. It is unambiguous about the operation, though it doesn't explain what 'route details' includes or distinguish it from the many sibling 'get_*' tools like get_request or get_timeline.
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?
There is no guidance about when to use this tool versus alternatives. The description simply states what it does, with no mention of prerequisites, typical scenarios, or exclusions. An agent must guess when route details are needed instead of the other request-related 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the conceptual purpose and does not mention authentication requirements, side effects, read-only status, or output behavior. The verb 'get' weakly implies a read operation, but this is not explicit or sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with the core action front-loaded and no redundant words. It is compact, though it is also minimal enough that it reads almost like an expansion of the tool name rather than a fuller definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six parameters and no annotations or output schema, the description is too sparse to be contextually complete. It omits authentication context, what the returned session data looks like, and when this tool should be chosen over closely related get_* tools.
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 schema already documents all six parameters. The description adds no parameter-level meaning beyond what the schema provides, such as how 'keys' relates to session data or how token/password authentication is intended to work.
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 verb 'Get' and the resource 'session data for a request', which is a specific action. However, it does not elaborate on what session data consists of or how it differs from sibling tools like get_request or get_auth_user, so differentiation is left mostly to inference.
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 when-to-use or when-not-to-use guidance is provided, and no alternative tools are mentioned. An agent gets no help deciding between this and the many similar get_* tools beyond the one-line resource statement.
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 of behavioral disclosure. It indicates a read-only operation with 'Get,' but it does not explain authentication expectations, whether the timeline is loaded from a remote server or local storage, what happens when the request ID is invalid, pagination, or response shape. For a tool with zero annotation support, this is a notable 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 a single, front-loaded sentence with no redundant words or filler. It communicates the core action and target resource efficiently, making it easy for an agent to parse quickly. Nothing in the phrasing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no annotations, no output schema, and many sibling tools, the description is too sparse to fully orient an agent. It doesn't explain the timeline concept, the authentication context, response expectations, or when this tool is preferable over analogous siblings like get_events. The description is minimally viable but leaves significant 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 documents all 5 parameters (100% coverage), including descriptions for authentication fields and requestId. The description adds little beyond the obvious resource association, but since the schema already covers parameter meaning thoroughly, 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 states a specific verb ('Get') and resource ('timeline events for a request'), which is clear and actionable. However, it does not differentiate from sibling tools like get_events or get_request, so some ambiguity remains about what makes timeline events distinct from event retrieval generally.
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?
There is no guidance on when to use this tool versus the many sibling tools, no mention of prerequisites (e.g., establishing a Clockwork connection or providing credentials beyond the request ID), and no explicit exclusions. Usage must be inferred entirely from the name and description.
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?
There are no annotations, so the description carries the full burden of disclosing behavioral traits. It only says 'Get rendered views' and does not explain what 'views' includes, whether authentication is needed, whether the operation is read-only, or what happens when no views exist. This is a meaningful transparency 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words and the core action is front-loaded. However, it is so brief that it borders on under-specification, missing useful context that would not bloat the description if added.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description is the only source of behavioral and contextual information, yet it omits when to use the tool, how results are returned, whether setup is required, and how this relates to the broader Clockwork workflow. It is not complete enough for an agent to invoke it confidently in 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 description coverage is 100%, so every parameter including requestId, token, baseUrl, password, and username is already described in the schema. The description adds no parameter-level meaning beyond the schema, which fits the baseline of 3 for full coverage.
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 states a clear verb and resource: 'Get rendered views' for a request. It is distinct enough to convey the core function, but it does not explicitly distinguish get_views from the many sibling tools that also retrieve request-related data, such as get_request or get_timeline.
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 about when to use this tool versus alternatives, whether a prior connection or authentication is required, or whether it should be called after a request is selected. The agent is left to infer usage entirely from the terse description and schema.
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 of behavioral disclosure. It only says 'list' and 'optional filtering'; it does not mention authentication requirements, pagination behavior, ordering, or result format. 'List' implies read-only, but that is not explicit and there is no output 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 a single front-loaded sentence with no wasted words. It communicates the core operation and filtering capability efficiently, even if it is too brief operationally.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 11 parameters, no annotations, and no output schema, this description is too thin. It does not establish Clockwork connection/auth expectations, result ordering, pagination behavior, or how this listing relates to get_queue_job. An agent would need to infer too much to invoke it confidently.
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 are already well documented. The description's 'optional filtering' generically aligns with the filter parameters but adds no extra meaning about how they interact or about pagination behavior.
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 uses the specific verb 'List' and the resource 'queue jobs', with 'optional filtering' adding the key behavior. It is clearly about listing rather than getting a single job, though it does not explicitly contrast with the get_queue_job sibling.
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?
There is no guidance about when to use this tool versus get_queue_job, list_commands, or other siblings. The intended context must be inferred from the tool name and sibling list, with no mention of prerequisites such as connecting to Clockwork first.
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 alone must disclose behavioral traits, but it only says the tool lists recent filtered requests. It does not mention authentication requirements (password, token, username), pagination via limit/offset, base URL handling, result ordering, or what 'recent' means, leaving significant behavioral uncertainty for a 12-parameter tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no wasted words and front-loads the primary action and resource. It is concise, though it is perhaps too brief to carry the usage and behavioral guidance a tool of this complexity needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 12 optional parameters, no annotations, no output schema, and many closely related sibling tools, the description is not complete enough. An agent still needs to infer authentication behavior, pagination defaults, recency boundaries, and when to use a different list/search 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 schema describes all 12 parameters with 100% coverage, so the description does not need to restate them. The description adds only the general 'optional filtering' framing, which is light but acceptable given the schema already documents each parameter's meaning.
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 uses a specific verb and resource ('List Clockwork requests') and adds the optional filtering qualifier, so an agent can tell it is a request-listing operation. However, it does not distinguish this tool from the sibling search_requests or get_latest_request, both of which overlap in function.
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?
There is no guidance about when to choose list_requests over alternatives such as search_requests or get_latest_request. The phrase 'optional filtering' implies a general listing use case, but no explicit context, exclusions, or sibling comparisons are provided.
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 behavioral disclosure. It indicates a read-only list operation, but does not disclose sorting behavior, pagination semantics beyond schema defaults, authentication requirements, or what fields are included in each test execution. The absence of these details leaves significant room for agent uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler words, achieving high conciseness. It front-loads the core action and resource. However, it is so terse that 'with optional filtering' adds little substance and could be seen as slightly redundant given the schema already documents filter parameters.
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 tool with 10 parameters, no annotations, and no output schema, this description is minimally adequate but not complete. The schema covers parameter semantics, but the description does not explain return shape, default ordering, pagination behavior, or the authentication context that the presence of username/password/token parameters implies. An agent could invoke it correctly with schema help, but not optimally.
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% and every parameter already has a clear description, so the baseline is 3. The tool description adds no extra parameter meaning beyond the generic 'optional filtering' phrase. This is acceptable because the schema fully 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 states a specific verb ('List') and resource ('test executions'), which clearly identifies the tool's core function. It is distinguishable from siblings like get_test by the plural 'list' semantics, though it does not explicitly differentiate itself. The phrase 'with optional filtering' is generic but not misleading.
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 gives no guidance on when to use this tool versus alternatives such as list_requests or get_test. It does not mention prerequisites like authentication via connect_clockwork, nor does it explain when filtering would be appropriate. There are no exclusions or alternative routing instructions provided.
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?
There are no annotations, so the description carries the full burden. 'Detect' implies a read-only analysis, but the description does not disclose what thresholds or patterns are used, whether any state is changed, or what the output looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded and contains no filler, but it is minimal to the point of under-specifying a tool with 10 parameters and no output schema. It is concise but not especially informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters, no annotations, and no output schema, the description should explain the result format and prerequisites such as Clockwork connection or authentication. It only states the detection goal, leaving an agent to guess how the analysis is scoped and returned.
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 all 10 parameters already have descriptions in the schema. The tool description adds no meaningful parameter detail beyond the word 'request', which loosely maps to requestId or uri scoping.
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 names a specific action and resource: 'Detect N+1 query patterns in a request.' It is clear about what the tool does, but it does not differentiate it from siblings like analyze_slow_queries or get_queries.
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 the tool should be used when N+1 query detection is needed, but it does not state when to prefer it over alternatives or how to scope the analysis. No exclusions or alternative tool references are provided.
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 behavioral disclosure. It states 'List' implying a read operation, but it does not clarify authentication needs (username, password, token), pagination behavior, response format, or whether only profiled executions are returned and what that entails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant wording, and it front-loads the core list action. However, it is slightly too terse to provide meaningful structure beyond the resource name, so it earns a 4 rather than a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with nine parameters, no output schema, and a large sibling set, the description is insufficiently complete. It does not describe return values, pagination, authentication context, or how this list relates to get_command, leaving agents without enough context to invoke it correctly beyond parameter names.
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 are already documented in the schema. The description adds no additional parameter meaning, which is acceptable given the baseline of 3 for 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 uses a specific verb 'List' and a clear resource: 'profiled Artisan command executions.' It clearly distinguishes this from sibling tools like get_command, list_requests, and list_queue_jobs, making the tool's purpose immediately understandable.
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 given about when to use this tool versus alternatives such as get_command for a single command execution or other list_* siblings. The context is only implied by the resource name, with no explicit when-to-use or when-not-to-use instructions.
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 behavioral disclosure. It communicates that the tool analyzes and groups exceptions, but it does not disclose defaults, time windows, aggregation behavior beyond grouping, whether it is read-only, or what the output structure looks like. This is thin for an 11-parameter tool.
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 efficient sentence with no filler. It front-loads the core purpose and grouping behavior, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite complete parameter schemas, the tool has no annotations and no output schema, and it has 11 parameters including authentication. The description does not address default time windows, the relationship between all/count/requestId, output shape, or when to prefer this over sibling analysis tools. Given the complexity, the description is not complete enough.
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 schema already documents every parameter. The description's 'grouping by message pattern' adds slight reinforcement to the groupByMessage parameter but does not materially augment 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 states a specific verb ('Analyze'), a clear resource ('exceptions across requests'), and a distinct behavior ('groupping by message pattern'). This clearly differentiates it from siblings like analyze_slow_queries or detect_n_plus_1, which operate on 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 gives no guidance on when to use this tool instead of related analytics tools, nor any exclusions. It does not mention alternatives, prerequisites, or typical scenarios. The parameter descriptions hint at usage, but the description itself provides no explicit when-to-use context.
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?
There are no annotations, so the description carries the full burden of explaining behavior. 'Detect' implies read-only analysis, but the description does not disclose what the tool does with detected issues, whether it mutates anything, what qualifies as high memory usage, or what kind of output the agent should expect.
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, tight sentence with no filler or redundant wording. It front-loads the core purpose and earns its place, even though brevity comes at the cost of behavioral detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a non-trivial tool with 11 parameters, no output schema, and no annotations, yet the description provides only a one-line purpose. An agent would not know what result to expect, how thresholdMB and detectGrowth interact, or how the tool relates to other diagnostic tools; this is incomplete for reliable 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?
Schema description coverage is 100%, so each of the 11 parameters already has a meaningful description in the schema. The tool description itself adds no parameter-level context, but the baseline of 3 is appropriate because the schema does the heavy lifting.
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 'Detect high memory usage and growth patterns' names a specific activity and resource, and clearly relates to memory diagnostics rather than the sibling tools that focus on slow queries, N+1 problems, or exceptions. However, it does not explicitly state that this operates on Clockwork HTTP request data, leaving a small ambiguity about the exact input 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 wording implies the tool should be used when investigating memory usage or growth patterns, but it gives no explicit when-to-use or when-not-to-use guidance. It also does not mention any alternative tools, which is a notable gap given the large sibling list.
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 behavioral disclosure burden. 'Get' implies a read-only operation and 'full details' indicates that it returns a richer representation, but the description does not touch on authentication requirements, failure behavior, or whether a connection must already exist.
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 tight sentence with the action front-loaded. It contains no filler, redundant qualifiers, or restatement of the tool name.
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 is minimally adequate for a simple getter, but it leaves important context implicit: how to obtain the requestId (presumably via list_queue_jobs), whether authentication parameters are mandatory, and what 'full details' means given there is no output schema. It is not misleading, but an agent must rely on sibling names and the schema to fill in the 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?
All five parameters are already described in the input schema, including requestId as the Clockwork request ID, so the schema does the semantic heavy lifting. The description adds no additional meaning about how the parameters relate to queue jobs beyond what the schema already provides.
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 uses a specific verb ('Get') and a specific resource ('queue job'), and 'full details' signals this is the detailed-view counterpart to list_queue_jobs. It is clear enough to distinguish from get_request and list_queue_jobs, though it does not explicitly reference those siblings or mention that the queue job is identified by requestId.
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?
There is no guidance about when to use this tool instead of list_queue_jobs, get_request, or other siblings. The description does not mention prerequisites such as an active Clockwork connection, how to obtain the requestId, or when a queue-job-specific view is needed.
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 the full behavioral disclosure burden, but it only states the filtering capability. It does not mention authentication prerequisites, pagination behavior, read-only nature, or the shape of returned results, all of which are relevant given the many auth and pagination parameters.
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 with no filler, and the key verb and filter dimensions are front-loaded. Every word contributes to stating the core function.
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 schema fully documents parameters, which helps, but the lack of an output schema and annotations leaves gaps around return value shape and auth flow. The description is adequate for a basic search call but does not fully prepare an agent for behavior beyond filtering.
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 11 parameters. The description merely recaps a few of those filters without adding extra meaning, format details, or relationships between 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 states the operation ('Search requests') and the resource ('requests') with a concrete set of filter dimensions: controller, URI, status, or duration. It is clear and specific, but it does not explicitly distinguish this tool from siblings like list_requests, get_request, or get_latest_request.
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 filter list implies this tool is for finding requests by criteria, so an agent gets a reasonable hint about when to use it. However, there is no explicit guidance about when to prefer search_requests over list_requests or get_latest_request, and no exclusions or conditions are provided.
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?
There are no annotations, so the description carries the burden of behavioral disclosure. 'Get' clearly implies a read-only retrieval and 'full details' signals a comprehensive response, but it does not explicitly state that there are no side effects, whether authentication is required, or what kind of data is included. It is minimally adequate but adds little context beyond the tool name.
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 focused sentence with no filler. It is appropriately concise and front-loads the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is thin: it omits how requestId relates to a test, how to obtain that ID (e.g., from list_tests), and what the returned details include. The phrase 'full details' is vague and leaves the agent without enough context 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?
Schema description coverage is 100%, so the schema already documents all five parameters. The description adds no new parameter meaning and doesn't clarify how requestId relates to a test execution, but the schema's 'Clockwork request ID' provides an adequate baseline.
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 uses a specific verb ('Get') and resource ('full details of a test execution'), clearly indicating a single-record retrieval. It distinguishes from the sibling list_tests (list vs full details), though it doesn't explicitly name alternatives. The term 'test execution' is reasonably specific but could be clearer about whether this maps to a Clockwork request.
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: after listing tests, get full details of one test execution. However, it gives no explicit when-to-use, no pointer to list_tests as the way to find the requestId, and no exclusions to distinguish it from get_request or other retrieval 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?
There are no annotations, so the description must convey behavior, and 'Get full details' does indicate a read operation that returns a comprehensive representation. However, it does not disclose authentication requirements, error handling, or what exactly constitutes 'full details'.
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, front-loaded sentence that immediately states the action and object. There is no filler or redundant explanation; every word contributes to the meaning.
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 straightforward get-by-ID tool, the description plus a fully documented schema are mostly sufficient. However, the lack of an output schema and annotations leaves the meaning of 'full details' unspecified, and the authentication parameters are only explained in the schema, not in the tool's usage 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?
All five parameters have descriptive schema entries, so the baseline is 3. The description adds only that requestId is the lookup key, which is already clear from the schema's 'Clockwork request ID' description.
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?
States a specific verb ('Get') and resource ('request'), and scopes it to a single request by ID, which distinguishes it from list_requests and get_latest_request. It could be stronger by naming those siblings, but the specificity is clear.
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 'by ID' implies the tool is for retrievals when a specific request identifier is already known. No explicit when-not-to-use guidance or alternative tools are mentioned, so the usage context is only implied.
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 burden of behavior. It clearly indicates a read-only retrieval operation and scopes it to a request, but it does not disclose output format, whether an active Clockwork connection is required, or what happens when no outgoing requests are found. 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 a single nine-word sentence with no filler. It front-loads the action and resource, making it immediately scannable and easy for an agent 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?
For a simple read tool with one required parameter and fully documented parameters, the description is largely complete. It states what is returned (outgoing HTTP requests) and the scope (during a request). It does not describe the return structure, but there is no output schema and the tool is simple enough that this is a minor gap.
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%, and the description itself adds no parameter-level meaning beyond the schema. Baseline 3 applies because the schema already documents all five parameters, including the required requestId.
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 names a specific verb ('Get'), a specific resource ('outgoing HTTP requests'), and a clear scope ('made during a request'). This distinguishes it from sibling tools like get_queries, get_redis_commands, and get_events without needing to reference them.
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 gives the context that the data belongs to a specific request, but it does not explain when to use this tool versus the many sibling retrieval tools, nor does it mention any exclusions or prerequisites. An agent is left to infer that this is only for outgoing HTTP requests.
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 behavioral disclosure burden. It transparently discloses the key behavioral fact that this tool is a stub and not available in Clockwork, so agents can infer it will not return real data. It does not describe what exactly happens when called, but the most important limitation is stated.
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 one short sentence that front-loads the intended operation and immediately follows with the critical availability caveat. Every word earns its place and nothing is redundant.
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 essential fact that the tool is a stub is present, which is important given no output schema. But the description does not suggest what to do instead or what response to expect if the tool is called anyway. Pointing to a working alternative like get_xdebug_hotspots would make it 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 sole parameter requestId is already fully documented in the schema with 100% coverage. The description adds no meaningful parameter semantics beyond what the schema provides, 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 states a specific operation: 'Get Xdebug profiling data for a request', clearly identifying the resource and action. It does not explicitly contrast with related siblings like get_xdebug_hotspots, but the core purpose is unmistakable despite the availability caveat.
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 'stub - not available in Clockwork' is an explicit warning that this tool should not actually be used, providing a clear when-not-to-use signal. However, it does not name an alternative such as get_xdebug_hotspots, so it stops short of giving complete routing 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, the description carries the behavioral disclosure burden. It clearly discloses that the tool is a 'stub' and 'not available', which is critical behavioral information beyond the basic action. It does not detail what happens on invocation, but the unavailability warning is the most important trait.
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 operation and immediately adds the availability caveat. There is no redundant wording 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?
For a simple two-parameter tool with full schema coverage, the description provides the essential purpose and a clear availability constraint. It lacks return-value information, but since the tool is flagged as unavailable, no further invocation detail is necessary for selection.
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 describes both parameters with 100% coverage, so the baseline is 3. The description adds minimal semantic value by tying hotspots to 'a request', which loosely maps to requestId, but does not explain limit or format beyond the schema.
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 identifies the operation ('Get Xdebug hotspots') and the target resource ('for a request'). It is immediately distinguishable from sibling tools like get_xdebug_profile, though it doesn't explicitly name or contrast a sibling.
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 explicitly states 'not available in Clockwork', which serves as a strong when-not-to-use signal. However, it does not suggest an alternative tool or provide positive usage conditions, so it stops short of full 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?
No annotations are provided, so the description carries the full behavioral burden. It discloses that the tool verifies API reachability and authentication, and that it caches the connection for later calls. This is meaningful operational detail, though it does not cover error behavior or cache lifetime.
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 with no wasted words. The primary action and verification behavior are front-loaded, and the note about sibling tools earning its place by preventing unnecessary connect calls.
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-required-parameter setup tool with fully documented schema, the description covers purpose, verification, caching, and the alternative invocation pattern. It does not explicitly describe the case when no parameters are provided, but the param descriptions already reference environment/local storage fallback.
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 documents all four parameters at 100% coverage, so the baseline is 3. The description groups the parameters and notes they are shared with sibling tools, which is useful cross-tool context, but it does not add deeper meaning about format, precedence, or edge cases 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 opens with a specific verb and resource: 'Connect to a Clockwork application', and immediately clarifies the optional password aspect. It clearly distinguishes this tool from the sibling data-retrieval tools by framing it as the connection-setup action.
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?
It states that the connection is cached for subsequent calls and that all other tools accept the same parameters directly, giving the agent a clear alternative. It does not explicitly spell out when to choose connect_clockwork over direct parameter passing, but the caching benefit is strongly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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