SKILLEMALL.ai

CD harness-generate-iOS

Auto-generate the full Claude Code harness for an iOS project (CLAUDE.md, docs/, README quick-cards, .claude/rules/). Default scans the entire project; pass a module path to process a single module. Triggers: harness-generate-iOS, generate harness, init harness. iOS/Swift projects only.

ClawHub Agent Skills author: Dian v1.0.1 MIT-0 4 files body ≈ 2 753 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Auto-generate the full Claude Code harness for an iOS project (CLAUDE.md, docs/, README quick-cards, .claude/rules/). Default scans the entire project; pass a…

As a process D 48/100 · Unfinished process — References files that are not bundled: path

GeneratorAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
82/100
safety, quality, tests
Safety 60%
95
Quality 40%
63
Run on models
none yet
Process rating
D
48/100
Unfinished process
References files that are not bundled: path
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 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 Obfuscation uni-zero-width references/templates.md:61
    Zero-width / invisible characters (possible hidden text) (4 occurrences) (a stray character, not a sequence)
    ```␀bash
    stray character

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: path

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: path
  • 0Tools and files. 1 referenced file(s) missing: path
  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 85Steps. 38 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2753 tokens
  • 100Running it twice. Mutating operations check current state

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)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 287: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 38 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This iOS harness generator is mostly coherent, but it requires persistent agent-memory changes that can affect future sessions without clear opt-in.
LLM: suspicious (high) · VirusTotal: · 12 Sept 2026