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agent-v3-performance-engineer

Agent skill for v3-performance-engineer - invoke with $agent-v3-performance-engineer

42

3.20x
Quality

12%

Does it follow best practices?

Impact

96%

3.20x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.agents/skills/agent-v3-performance-engineer/SKILL.md

The canonical home for this skill is agent-v3-performance-engineer in ruvnet/claude-flow

SKILL.md
Quality
Evals
Security

Quality

Content

25%Weight 40%Scale 1-5

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

The body presents an ambitious performance-engineering plan but does so as verbose, decorative scaffolding: ASCII boxes, emoji headers, and unimplemented TypeScript class stubs rather than executable guidance, with no multi-file structure and no validation feedback loops for its batch/regression operations. It lands near the low end across all content dimensions.

Suggestions

Replace the TypeScript class stubs with concrete, runnable benchmark commands or minimal working scripts, or explicitly mark them as illustrative pseudocode with a justification.

Add explicit validation checkpoints and a validate -> fix -> retry feedback loop to the regression-detection and benchmark workflows.

Split the per-domain benchmark suites into separate reference files (e.g. references/flash-attention.md, references/search.md) and keep SKILL.md as a lean overview with one-level-deep links.

DimensionReasoningScore

Conciseness

The body is noticeably verbose: ASCII-art boxes, emoji headers, and large TypeScript class skeletons (StartupBenchmarks, MemoryBenchmarks, SwarmBenchmarks, etc.) repeat the same target numbers multiple times and explain concepts Claude already knows, matching the 'noticeably verbose; several unnecessary explanations or padded sections' anchor.

2 / 5

Actionability

The TypeScript examples are class shells with undefined methods (initializeCLI, spawn15Agents, coordinateSwarmTask, hnswSearch, flashAttention), so they are scaffolding rather than executable code, sitting between the 'minimal concrete guidance' and 'pseudocode instead of executable code' anchors and leaning down because no method is actually implemented.

2 / 5

Workflow Clarity

There is a rough sequence (benchmark suites run, regression detection compares to baseline) but no explicit validation checkpoints or error-recovery feedback loops for batch benchmark and regression operations; per the rubric's feedback-loop cap this cannot exceed 3, and the sparse checkpointing fits the 'rough sequence present but many gaps; validation absent' anchor.

2 / 5

Progressive Disclosure

The skill is a monolithic single file with no bundle files (references/, scripts/, assets/ do not exist) and all six large benchmark suites inlined, so content that clearly belongs in separate files is inlined, matching the 'content that clearly belongs in separate files is inlined' anchor.

2 / 5

Total

8

/

20

Passed

Description

0%Weight 40%Scale 1-5

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 frontmatter description is a placeholder-style template that communicates only the skill's internal name and invocation token, with no concrete capabilities, user-facing triggers, or usage guidance. It scores at the floor on every dimension.

Suggestions

Replace the description with concrete actions the skill performs, e.g. 'Benchmarks and optimizes claude-flow v3 performance: Flash Attention speedup, AgentDB HNSW search, memory reduction, and startup latency.'

Add an explicit 'Use when...' clause stating the natural trigger phrases (e.g. 'Use when validating performance targets, running benchmark suites, or investigating regressions').

Drop the invocation token and role label from the description; describe what the skill does in third person using terms a user would actually say.

DimensionReasoningScore

Specificity

The description ("Agent skill for v3-performance-engineer - invoke with $agent-v3-performance-engineer") names no concrete actions whatsoever, only the skill's own role label and an invocation token, matching the 'entirely vague; no concrete actions' anchor.

1 / 5

Completeness

It fails to answer either 'what does this do' (only says it is an 'agent skill for' a role) or 'when should Claude use it' (no 'Use when...' clause), matching the 'missing both what and when' anchor.

1 / 5

Trigger Term Quality

It contains no natural keywords a user would say; only the internal skill name and the invocation token '$agent-v3-performance-engineer' appear, which is technical scaffolding rather than natural language, matching the 'no natural keywords; only technical jargon' anchor.

1 / 5

Distinctiveness Conflict Risk

The phrasing is an entirely generic template that could apply to any agent skill, offering no niche or distinguishing triggers, matching the 'entirely generic; would conflict with virtually any skill' anchor.

1 / 5

Total

4

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
ruvnet/ruflo
Reviewed

Table of Contents

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