analyzing-network-latency
Analyze network latency and optimize request patterns for faster communication. Use when diagnosing slow network performance or optimizing API calls. Trigger with phrases like "analyze network latency", "optimize API calls", or "reduce network delays".
54
44%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/performance/network-latency-analyzer/skills/analyzing-network-latency/SKILL.mdQuality
Discovery
89%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 when to use the skill with explicit trigger phrases and a well-defined 'when' clause. Its main weakness is that the 'what' portion could be more specific about the concrete actions performed (e.g., measuring latency, batching requests, caching strategies). Overall it performs well for skill selection purposes.
Suggestions
Add more specific concrete actions to improve specificity, e.g., 'Measures round-trip times, identifies bottlenecks, batches API requests, and implements retry strategies for faster communication.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (network latency, request patterns) and some actions (analyze, optimize), but doesn't list multiple concrete specific actions. 'Analyze network latency' and 'optimize request patterns' are somewhat vague—it doesn't specify what concrete techniques or outputs are involved (e.g., measure round-trip times, batch API requests, implement connection pooling). | 2 / 3 |
Completeness | Clearly answers both 'what' (analyze network latency and optimize request patterns) and 'when' (diagnosing slow network performance, optimizing API calls) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would say: 'analyze network latency', 'optimize API calls', 'reduce network delays', 'slow network performance'. These cover common variations of how users would describe this need. | 3 / 3 |
Distinctiveness Conflict Risk | The description targets a clear niche—network latency analysis and request pattern optimization—with distinct trigger terms that are unlikely to conflict with other skills like general code optimization or API design skills. | 3 / 3 |
Total | 11 / 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 descriptive rather than instructive. It explains what network latency analysis is and describes what Claude would do at a high level, but provides zero executable code, specific commands, or concrete techniques. The content is heavily redundant across sections and wastes tokens on concepts Claude already understands.
Suggestions
Replace abstract descriptions with concrete, executable code examples — e.g., Python scripts using aiohttp for parallel requests, connection pooling with requests.Session, or curl commands for latency measurement.
Consolidate redundant sections (Overview, How It Works, When to Use, Instructions) into a single concise workflow with specific commands and validation checkpoints at each step.
Add actual before/after code examples showing specific optimizations (e.g., converting serial requests to asyncio.gather, implementing request batching with specific batch size recommendations).
Remove sections that explain concepts Claude already knows (what connection pooling is, what batching means) and replace with specific implementation patterns and thresholds for decision-making.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and padded with unnecessary context. The 'Overview' restates the title, 'How It Works' and 'When to Use' sections explain things Claude already knows, and the examples describe what the skill 'will do' rather than providing actionable instructions. Multiple sections are redundant (e.g., 'How It Works' vs 'Instructions'). | 1 / 3 |
Actionability | No concrete code, commands, or executable examples anywhere. Everything is abstract description — 'identify all network requests,' 'analyze the latency,' 'suggest parallelizing' — without any actual tools, scripts, code snippets, or specific commands to run. The examples describe what the skill 'will do' rather than showing how. | 1 / 3 |
Workflow Clarity | The 'Instructions' section lists steps but they are vague and lack any validation checkpoints, specific tools/commands, or feedback loops. Steps like 'Identify all network requests' and 'Measure latency for each request type' provide no concrete guidance on how to accomplish them. No error recovery or verification steps are integrated into the workflow. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files and no bundle files to support it. Content is poorly organized with redundant sections (Overview, How It Works, When to Use, Examples, Instructions all overlap significantly). The 'Resources' section lists generic topic names without actual links or file references. | 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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