SKILLEMALL.ai

BF strategy-workflow

Comprehensive strategy development workflow from ideation to validation. Use when creating trading strategies, running backtests, parameter optimization, or walk-forward validation.

ClawHub Agent Skills author: Dan Repaci v0.1.0 4 files body ≈ 2 001 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 38/100 · Will not run — References files that are not bundled: scripts/process_auditor.py

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: scripts/process_auditor.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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Edit Bash Glob Grep

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/process_auditor.py

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: scripts/process_auditor.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/process_auditor.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 72 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2001 tokens
  • low 10 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)
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 181: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 72 items
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This trading backtesting skill is mostly documentation, but it asks agents to run persistent autonomous watchdogs, kill and relaunch workers, use root SSH on remote servers, and back up results to cloud destinations without strong user-control boundaries.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026