analyzing-system-throughput
Analyze and optimize system throughput including request handling, data processing, and resource utilization. Use when identifying capacity limits or evaluating scaling strategies. Trigger with phrases like "analyze throughput", "optimize capacity", or "identify bottlenecks".
40
41%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/performance/throughput-analyzer/skills/analyzing-system-throughput/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid description that clearly communicates both what the skill does and when to use it, with explicit trigger phrases. Its main weakness is that the capabilities described are somewhat broad and category-level rather than listing specific concrete actions, and there is moderate overlap risk with related performance/infrastructure skills.
Suggestions
Add more specific concrete actions to improve specificity, e.g., 'measure requests per second, profile queue depths, calculate saturation points, model horizontal vs vertical scaling tradeoffs'.
Differentiate more clearly from adjacent skills (e.g., general performance profiling, infrastructure monitoring) by specifying what this skill does NOT cover or by narrowing the scope.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (system throughput) and lists some actions (analyze, optimize, request handling, data processing, resource utilization), but these are still somewhat broad and not as concrete as specific operations like 'extract tables' or 'fill forms'. The actions described are more like categories than discrete tasks. | 2 / 3 |
Completeness | Clearly answers both 'what' (analyze and optimize system throughput including request handling, data processing, and resource utilization) and 'when' (identifying capacity limits, evaluating scaling strategies) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes explicit trigger phrases like 'analyze throughput', 'optimize capacity', and 'identify bottlenecks', plus natural keywords such as 'scaling strategies', 'capacity limits', and 'resource utilization'. These are terms users would naturally use when seeking this kind of help. | 3 / 3 |
Distinctiveness Conflict Risk | While 'throughput' and 'bottlenecks' are somewhat distinctive, terms like 'optimize', 'resource utilization', and 'scaling strategies' could overlap with general performance optimization, infrastructure, or DevOps skills. The niche is reasonably clear but not sharply delineated. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is almost entirely abstract description with no actionable content. It reads like a product marketing document rather than an instruction set—describing what the skill does conceptually without ever providing concrete commands, code, metrics queries, or tool invocations. The content is heavily padded with sections that explain obvious concepts and repeat the same vague ideas in different formats.
Suggestions
Replace abstract descriptions with concrete, executable examples: show actual commands or code for collecting throughput metrics (e.g., specific CLI tools, API calls, or script invocations with real syntax).
Remove redundant sections (Overview, How It Works, When to Use, Best Practices, Integration, Resources) and consolidate into a lean workflow with specific steps, expected outputs, and validation checkpoints.
Add concrete examples with sample input data and expected output format (e.g., a sample throughput report JSON schema or table format).
Define the 'throughput-analyzer' plugin with actual usage syntax, or remove the reference if it doesn't exist, and instead provide real tool commands for metrics collection and analysis.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive explanation of concepts Claude already knows. The 'Overview', 'How It Works', 'When to Use', 'Best Practices', 'Integration', and 'Resources' sections are all filler that explain obvious things without adding actionable value. The skill could be reduced to a fraction of its size. | 1 / 3 |
Actionability | No concrete code, commands, or executable guidance anywhere. The examples describe what 'the skill will' do in abstract terms rather than providing actual analysis steps, metrics queries, or tool invocations. References to a 'throughput-analyzer' plugin with no concrete usage syntax or API. The instructions are a vague numbered list with no specifics on how to actually perform any step. | 1 / 3 |
Workflow Clarity | The workflow steps ('Identify critical components', 'Collect metrics', 'Analyze resource saturation') are entirely abstract with no concrete actions, no validation checkpoints, and no feedback loops. There's no guidance on what tools to run, what output to expect, or how to verify results at each step. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files despite mentioning a metrics directory path. Multiple redundant sections (How It Works, Instructions, Examples) cover similar ground without clear hierarchy. No bundle files exist to support the referenced path '${CLAUDE_SKILL_DIR}/metrics/throughput/'. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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