SKILLEMALL.ai

BF modular-skills

Build composable skill modules with hub-and-spoke loading. Use when token budget is tight.

athola/claude-night-market Hermes author: athola 11 files body ≈ 1 376 tokens Open the sourcegithub.com analyzed 3 h ago

Build composable skill modules with hub-and-spoke loading.

As a process F 30/100 · Will not run — References files that are not bundled: ../../shared-modules/skill-selection-judgment.md, scripts/skill_analyzer.py

GeneratorDesigntype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
30/100
Will not run
References files that are not bundled: ../../shared-modules/skill-selection-judgment.md, scripts/skill_analyzer.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.
  2. The text references files that are not there: add them or drop the references.
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: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 90 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning missing-ref reference to a missing file: ../../shared-modules/skill-selection-judgment.md
  • warning missing-ref reference to a missing file: scripts/skill_analyzer.py
  • note frontmatter-key unknown frontmatter key "alwaysApply"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • 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 "modules"
  • note edit-residue the text marks something as outdated (lines 29): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 30/100

Will not run. References files that are not bundled: ../../shared-modules/skill-selection-judgment.md, scripts/skill_analyzer.py
  • 0Tools and files. 2 referenced file(s) missing: ../../shared-modules/skill-selection-judgment.md, scripts/skill_analyzer.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 85Steps. 19 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1376 tokens

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)
  • +3Description length 90: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.