Scalene-MCP

by ptmorris05

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action: creating profiles, listing them, analyzing, comparing, and managing project context. No two tools have overlapping responsibilities, and descriptions clearly differentiate their purposes.
Naming Consistency4/5
All tool names use snake_case and follow a verb or verb_noun pattern. However, 'analyze' and 'profile' are single-word verbs while others are multi-word, which is a minor inconsistency but still clear.
Tool Count5/5
With 7 tools, the server covers the essential profiling workflow: creation, listing, analysis, comparison, and project management. This count is well-scoped without being excessive or insufficient.
Completeness5/5
The tool surface covers the full lifecycle of profiling: profile creation, listing, detailed analysis, comparison, project file selection, and root configuration. No critical gaps are apparent for typical usage.
Average 4/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on January 17, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It discloses return format {root, type, markers_found} which adds value, but could explicitly state read-only nature and lack of side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no wasted words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no annotations, the description adequately specifies the return value and purpose. Could mention that no input is required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has no parameters (100% coverage trivial). Baseline score of 4 as per guidelines for 0 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?
Description states 'Get the detected project root and structure type' with clear verb and resource. It distinguishes from siblings like analyze or list_profiles, though no explicit differentiation is given.
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 on when to use this tool versus alternatives like set_project_context or list_project_files. The description only states what it does.
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?
The description states it returns a list of profile IDs, which is adequate for a simple listing operation. However, it does not disclose potential side effects (likely none), authorization needs, or any limitations like pagination. With no annotations, the description carries the full burden, and it meets minimal expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using two sentences to convey purpose and return format. No extraneous information, front-loaded with the core action.
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 zero-parameter listing tool, the description covers the essential purpose and output format. With an output schema existing (though not provided), the return type is covered. It is complete enough for the tool's simplicity, though could mention if only available for current session scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters (schema coverage 100% for empty params). The description adds value by explaining the return format, which goes beyond the schema. According to guidelines, 0 parameters warrant a baseline of 4, and the description compensates 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 clearly states the tool lists all captured profiles in the session and specifies the return format (list of profile IDs). It is specific with verb 'list' and resource 'profiles', but does not differentiate itself from sibling tools like 'profile' or 'compare_profiles'.
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 (e.g., 'profile' for a single profile, 'compare_profiles' for comparisons). It does not mention any prerequisites or contexts where listing is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes analysis as a read-like operation without side effects, but does not explicitly state non-destructiveness or address auth requirements, rate limits, or other behavioral traits. The return structure is outlined, but not all possible variations are detailed.
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 front-loaded with a clear purpose followed by a structured Args/Returns section. It is concise without extraneous words, though the parameter list could be slightly more streamlined.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, varied return structures), the description covers parameter semantics and basic return format. However, it lacks details on how each metric_type affects the output and does not reference sibling tools for context, leaving some gaps for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter: profile_id, metric_type with allowed values, top_n, thresholds, and conditional filename. It adds constraints and context not present in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes profiling data with flexible analysis types. It lists specific metric_type options and references the profile() tool for input, distinguishing it from siblings like compare_profiles or list_profiles.
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 after obtaining a profile_id from profile(), but does not explicitly say when to use versus alternatives like compare_profiles. No exclusions or when-not-to-use guidance 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?
No annotations are provided, so the description carries the full burden. It discloses that the tool compares two profiles (non-destructive, read operation) and returns a structured result with fields like runtime_change_pct and memory_change_pct. It does not discuss permissions, errors, or side effects, but the nature of the tool suggests no destructive behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a one-sentence purpose statement followed by parameter descriptions and return fields. Every sentence adds value, and it is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (comparison with multiple metrics) and the existence of an output schema, the description adequately covers the purpose, parameters, and return structure. It does not explain all fields in detail, but the output schema presumably provides those details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by labeling 'before_id' as from original code and 'after_id' from optimized code. However, it does not specify format, constraints (e.g., must exist), or validation rules beyond the schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compare two profiles to measure optimization impact.' It uses a specific verb ('compare') and resource ('profiles'), and it distinguishes itself from sibling tools like 'profile' (which likely runs profiling) and 'list_profiles' (which lists profiles).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (after obtaining two profile IDs, typically before and after optimization) and provides parameter roles ('before_id from original code', 'after_id from optimized code'). It does not explicitly state when not to use or mention alternatives, but the context from sibling names helps differentiate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses the return format (sorted relative paths) and parameters, but lacks details on side effects, permissions, performance, or handling of symlinks/hidden files. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences plus Args) with no fluff. Primary purpose is front-loaded, and the Args section is structured for readability. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of output schema (implied from description), the description covers the main functionality and return format. It could mention behavior for empty results or error cases, but overall complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains 'pattern' as glob, 'max_depth' as maximum depth, and 'exclude_patterns' as comma-separated patterns, adding meaning beyond schema defaults and types. Only minor omission: no mention of default excludes like .git.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'project files' with a specific scope 'matching pattern, relative to project root'. It distinguishes from sibling tools by specifying file listing, which none of the siblings do.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to list project files with glob patterns, but does not explicitly state when to use versus alternatives or provide exclusions. Since siblings are not file-listing tools, the intended use is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses behavioral traits: profiling mode via 'type', optional exclusions (cpu_only, include_*), thresholds, and return type. It does not mention permissions or side effects, but is transparent about options.
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 well-structured with a clear opening sentence and bullet list of parameters. It is slightly verbose but efficiently conveys information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 13 parameters and output schema, the description covers input semantics and return structure. It lacks guidance on error scenarios or performance implications, but is sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining each parameter's purpose concisely (e.g., 'cpu_only: Skip memory/GPU profiling'). This adds meaning beyond parameter names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool profiles Python code using Scalene, a specific verb-resource pairing. It distinguishes from siblings like analyze and compare_profiles.
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 lists parameters but offers no explicit guidance on when to use this tool versus siblings. Usage context is implied by the tool name, but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations; description mentions override behavior and returns structure, but lacks details on persistence or side effects. Adequate for simple setter.
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?
Very concise with purpose, usage, args, and returns. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter setter with output schema, description fully covers purpose, usage, parameter meaning, and return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema only gives type string; description adds 'absolute path' clarification, compensating for 0% 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?
Clearly states it sets the project root, overriding auto-detection. Differentiates from sibling 'get_project_root' which reads.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when auto-detection fails or gives wrong path, providing clear 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.

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