SKILLEMALL.ai

BF ai-qa-agent

AI QA Agent — the final quality gate before delivery. Tests code for correctness, verifies data integrity, checks brand voice compliance, and reviews document formatting. Use this skill whenever the user needs to review, verify, check, audit, inspect, or validate any deliverable before it ships. Triggers on requests like "review this", "check the code", "verify the data", "is this ready to send", "QA this", "does this match our brand voice", "final check", "sign off on this", or any task involving quality assurance, code review, data validation, copy editing, or pre-delivery verification. Make sure to use this skill whenever the user mentions reviewing, checking, verifying, approving, or doing a final pass on any deliverable — code, documents, data files, copy, or marketing assets — even if they don't explicitly say "QA". This agent works both standalone and as the downstream reviewer in the Staff Agent pipeline (Staff produces, QA reviews). NOT for: initial content creation (use ai-staff-agent), complex bug fixing (review and report, don't fix), or deployment verification.

ClawHub Agent Skills author: mattsteff-hope v1.0.0 MIT-0 4 files body ≈ 2 886 tokens Open the sourceclawhub.ai analyzed 2 d ago

AI QA Agent — the final quality gate before delivery.

As a process F 45/100 · Will not run — References files that are not bundled: references/brand-voice-guide.md

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
54
Run on models
none yet
Process rating
F
45/100
Will not run
References files that are not bundled: references/brand-voice-guide.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. 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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • error description-long description is 1091 chars, limit 1024
  • warning missing-ref reference to a missing file: references/brand-voice-guide.md

Process rating: all ten parameters 45/100

Will not run. References files that are not bundled: references/brand-voice-guide.md
  • 0Tools and files. 1 referenced file(s) missing: references/brand-voice-guide.md
  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 60Steps. 86 steps, 4 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2886 tokens

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

  • +3Description length 1090: 120–800 characters recommended
  • -5TODO / placeholder text left in the skill
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +4Description says when NOT to use the skill
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 86 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: clean
This skill is a coherent QA-review helper that reads deliverables and produces a report, with a disclosed but worth-noting local report file save.
LLM: benign (high) · VirusTotal: · 13 Jul 2026