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BB performance-review

Detects time and space complexity hotspots via AST scan. Use when code feels slow, before performance-sensitive merges, or to find O(n²) regressions.

athola/claude-night-market Hermes author: athola 6 files body ≈ 2 560 tokens Open the sourcegithub.com↗ analyzed 3 h ago

Detects time and space complexity hotspots via AST scan.

As a process B 67/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerQuality controlInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
B
67/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 149 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "alwaysApply"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "usage_patterns"
  • note frontmatter-key unknown frontmatter key "complexity"
  • note frontmatter-key unknown frontmatter key "model_hint"
  • note frontmatter-key unknown frontmatter key "estimated_tokens"
  • note frontmatter-key unknown frontmatter key "progressive_loading"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • note frontmatter-key unknown frontmatter key "modules"

Process rating: all ten parameters 67/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2560 tokens
  • low 13 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 149: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 38 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.