SKILLEMALL.ai

BD foreman-pro

Digital construction foreman: crew management, work acceptance, work logs, hidden works acts, safety, schedules and executive documentation.

ClawHub Agent Skills author: RAAIPRO v3.5.4 MIT-0 37 files · 3 scripts body ≈ 17 073 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
95
Quality 40%
50
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.

Obfuscation 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 files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 Obfuscation uni-mixed-script-word SKILL.md:405
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (1 occurrence)
    | Работа с эпоксидом/ЛКМ | ДА | ДА | ДА | А1P2 | ДА | — |

Files scanned: 36. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 17073 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "price"
  • note frontmatter-key unknown frontmatter key "price_currency"

Process rating: all ten parameters 43/100

  • 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
  • 10Execution cost. Instruction body is 17073 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (foreman-pro) differs from the folder (raai-foreman-pro)
  • 100Tools and files. No external tools needed
  • 100Steps. 196 steps
  • 100Running it twice. No mutating operations

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)
  • +4Structure: 1 headings, hard to scan
  • +3Output format is not stated: the model decides each time
  • -5Long text without headings
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • +3Description length 140: enough signal without eating the budget
  • +3Step-by-step instructions: 196 items
  • +4Has examples (22 code blocks)
  • +1License stated
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.

External checks

ClawHub: clean
This is a disclosed construction-foreman workflow package with local-only scripts and no evidence of hidden data theft, background persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026