SKILLEMALL.ai

BC pua-debugging

Forces exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology. MUST trigger when: (1) any task has failed 2+ times or you're stuck in a loop tweaking the same approach; (2) you're about to say 'I cannot', suggest the user do something manually, or blame the environment without verifying; (3) you catch yourself being passive — not searching, not reading source, not verifying, just waiting for instructions; (4) user expresses frustration in ANY form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', '换个方法', '为什么还不行', '你再试试', '加油', '你怎么又失败了', or any similar sentiment even if phrased differently. Also trigger when facing complex multi-step debugging, environment issues, config problems, or deployment failures where giving up early is tempting. Applies to ALL task types: code, config, research, writing, deployment, infrastructure, API integration. Do NOT trigger on first-attempt failures or when a known fix is already executing successfully.

ClawHub Agent Skills author: tanweai v1.0.0 MIT-0 2 files body ≈ 1 978 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationSoftware developmentInfrastructuretype 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
C
52/100
Has gaps
Result and completion w 14
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.
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

  • error description-long description is 1025 chars, limit 1024
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 53 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1978 tokens
  • 100Running it twice. No mutating operations
  • low 10 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)
  • +3Description length 1025: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -242 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 53 items
  • +4Has examples (1 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This instruction-only skill has no executable payload, but it broadly pressures the agent to take tool-heavy action and adopt a coercive persona across many ordinary tasks.
LLM: suspicious (high) · VirusTotal: · 29 May 2026