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performance-analysis

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

51

2.77x
Quality

27%

Does it follow best practices?

Impact

97%

2.77x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.claude/skills/performance-analysis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

22%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is excessively verbose, containing extensive sample outputs, CI/CD configurations, custom analysis scripts, and categorical lists that inflate the document without proportional value. While the CLI commands are concrete and actionable, the skill lacks proper multi-step workflows with validation checkpoints—critical for a performance analysis tool where misdiagnosis could lead to counterproductive optimizations. The content would benefit greatly from aggressive trimming and restructuring into a concise overview with referenced detail files.

Suggestions

Cut the document to under 100 lines by removing sample outputs, CI/CD YAML, custom scripts, and metric category lists—move these to referenced bundle files like EXAMPLES.md and CI-INTEGRATION.md

Add explicit sequenced workflows with validation steps, e.g.: 1. Run detection → 2. Review output → 3. Validate recommendations against current config → 4. Apply fixes incrementally → 5. Re-run detection to confirm improvement

Remove descriptive content Claude already knows (what cache hit rates are, what memory bottlenecks mean) and replace with decision-making heuristics (e.g., 'If utilization < 60%, reduce agent count before investigating other bottlenecks')

Consolidate the redundant output examples (CLI text output, JSON format, markdown report) into a single canonical example with a reference to a formats file

DimensionReasoningScore

Conciseness

Extremely verbose at ~400+ lines. Contains extensive lists of metrics categories, sample outputs, CI/CD YAML, custom scripts, best practices, and troubleshooting sections that are largely padded content. Much of this (e.g., explaining what 'cache hit rates' or 'memory access patterns' are, listing every possible bottleneck category) is knowledge Claude already has. The sample report output, sample JSON, and sample markdown report are all redundant ways of showing the same information.

1 / 3

Actionability

The CLI commands are concrete and copy-paste ready (e.g., `npx claude-flow bottleneck detect --fix --threshold 15`), and the MCP integration shows specific function calls. However, much of the content is descriptive rather than instructive—listing what metrics are analyzed, what report sections exist, and what typical improvements look like, without giving Claude clear decision-making guidance on when to use which approach.

2 / 3

Workflow Clarity

Despite being a complex multi-step analysis skill, there are no clear sequenced workflows with validation checkpoints. The 'Analyze and Auto-Fix' is a single command, not a workflow. The best practices section says 'always review before applying --fix' but never shows a concrete review-then-fix workflow. The troubleshooting section lists commands without sequencing them into diagnostic workflows with decision points.

1 / 3

Progressive Disclosure

The document references several external files in 'See Also' (bottleneck-detect.md, performance-report.md, etc.) and cross-references other skills, which is good structure. However, no bundle files are provided to verify these references exist, and the main SKILL.md itself is monolithic—containing extensive sample outputs, CI/CD configs, and custom scripts that should be in separate referenced files rather than inline.

2 / 3

Total

6

/

12

Passed

Description

32%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description identifies a specific domain (Claude Flow swarms) and lists high-level capabilities, but lacks a 'Use when...' clause, which is a significant gap for skill selection. The trigger terms are somewhat relevant but not comprehensive, and the actions described remain at a summary level rather than listing concrete, specific operations.

Suggestions

Add an explicit 'Use when...' clause with trigger scenarios, e.g., 'Use when the user asks about swarm performance, slow agents, task throughput, or wants to optimize a Claude Flow swarm configuration.'

Include more natural trigger terms users might say, such as 'slow swarm', 'agent bottleneck', 'swarm profiling', 'task latency', 'parallel execution performance'.

Make capabilities more concrete by specifying what is analyzed and what outputs are produced, e.g., 'Analyzes agent utilization, task queue depths, and inter-agent communication latency; generates flamegraph-style reports and actionable tuning suggestions.'

DimensionReasoningScore

Specificity

Names the domain (Claude Flow swarms) and lists some actions (performance analysis, bottleneck detection, optimization recommendations), but these are somewhat high-level and not fully concrete—e.g., it doesn't specify what kinds of bottlenecks, what metrics are analyzed, or what form recommendations take.

2 / 3

Completeness

Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also only moderately detailed, this scores at 1.

1 / 3

Trigger Term Quality

Includes relevant terms like 'performance analysis', 'bottleneck detection', 'optimization', and 'Claude Flow swarms', but misses common natural variations users might say such as 'slow swarm', 'swarm performance', 'profiling', 'latency', or 'throughput'.

2 / 3

Distinctiveness Conflict Risk

The mention of 'Claude Flow swarms' provides some niche specificity, but 'performance analysis' and 'optimization recommendations' are generic enough to potentially overlap with other performance-related or optimization skills.

2 / 3

Total

7

/

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.

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (581 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

9

/

11

Passed

Repository
ruvnet/ruvector
Reviewed

Table of Contents

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