SKILLEMALL.ai

BC orche

A multi-agent orchestration engine that systematically executes complex tasks in 4 phases (Query → Plan → Execute → Verify). Ensures high-quality deliverables through phase gates, Critic debates, 14-item hallucination checks, and automatic regression on verification failure.

ClawHub Agent Skills author: reikys v1.0.1 MIT-0 2 files body ≈ 9 408 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, when it triggers, execution cost

AnalyzerData and analyticsAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
C
63/100
Has gaps
When it triggers w 12
20
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 9408 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 63/100

  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 15 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 9408 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 175 steps, 1 vague phrases
  • 100Failures and branches. 7 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 26 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
  • -5TODO / placeholder text left in the skill
  • -2117 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 275: enough signal without eating the budget
  • +4Structure: 97 headings
  • +3Step-by-step instructions: 175 items
  • +4Has examples (32 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is an instruction-only orchestration skill whose multi-agent behavior is disclosed and mostly bounded, though users should be aware it can spawn agents, write local run state, and auto-proceed after initial approval.
LLM: benign (high) · VirusTotal: · 29 May 2026