SKILLEMALL.ai

CF 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.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Dian v1.0.1 MIT-0 4 files body ≈ 2 753 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 51/100 · Will not run — References files that are not bundled: path

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
74/100
safety, quality, tests
Safety 60%
82
Quality 40%
63
Run on models
none yet
Process rating
F
51/100
Will not run
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

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Obfuscation
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. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  3. 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

  • high Obfuscation uni-zero-width references/templates.md:61
    Zero-width / invisible characters (possible hidden text) (4 occurrences)
    ```␀bash

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 51/100

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
  • 70Failures and branches. 5 branches
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2753 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 is an iOS documentation-harness generator, but it should be reviewed because it makes broad project changes and writes persistent agent memory without a clear approval step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026