SKILLEMALL.ai

BA spawner

Instant agent hiring. Takes job postings from the orchestrator and fills them with properly configured sub-agents. Handles context passing, timeout enforcement, concurrent agent limits, and completion tracking. The bridge between scoping (orchestrator) and execution (sub-agents).

ClawHub Agent Skills author: KairoKid v1.0.0 MIT-0 2 files body ≈ 1 450 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process A 81/100 · Runs to the end — weak spots: consistency

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
A
81/100
Runs to the end
Consistency w 8
40
Tools and files w 18
60
When it triggers w 12
70
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: 2. 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")

Process rating: all ten parameters 81/100

  • 40Consistency. Frontmatter name (spawner) differs from the folder (venture-spawner)
  • 60Tools and files. Uses tools (git, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 39 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 4 branches, has a failure section
  • 100Execution cost. Instruction body is 1450 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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)
  • -230 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 280: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 39 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a disclosed sub-agent orchestration skill with high-impact capabilities, but its behavior is coherent with its stated purpose and no hidden code or exfiltration is evident.
LLM: benign (high) · VirusTotal: · 28 May 2026