SKILLEMALL.ai
RU Sign in

BC Travel Memory Preservation System

Systematic approach to preserving travel memories

ClawHub Hermes author: haidong v1.0.1 MIT-0 7 files body ≈ 1 997 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "language"

Process rating: all ten parameters 60/100

  • 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. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (Travel Memory Preservation System) differs from the folder (travel-memory-preservation-system)
  • 100Tools and files. No external tools needed
  • 100Steps. 97 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Execution cost. Instruction body is 1997 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 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)
  • +3Description length 49: 120–800 characters recommended
  • -222 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 97 items
  • +3Output format is stated explicitly
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: clean
This is a low-risk travel-memory planning skill that returns descriptive JSON guidance and does not show hidden access, persistence, network use, or destructive behavior.
LLM: benign (high) · VirusTotal: · 21 Jun 2026