SKILLEMALL.ai

BC omnidebug-autopilot

Autonomous end-to-end debugging skill for any codebase, language, and framework. Detects stack, reproduces failures, isolates root cause, applies minimal safe fixes, and verifies with tests/build/lint without user interruption.

ClawHub Hermes author: clarezoe v1.0.2 MIT-0 8 files body ≈ 1 618 tokens Open the sourceclawhub.ai analyzed 28 h ago

Autonomous end-to-end debugging skill for any codebase, language, and framework.

As a process C 58/100 · Has gaps — weak spots: when it triggers, inputs and preconditions

ProcedurePlaywrightSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
58/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Failures and branches w 10
50
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.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 227 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill

Process rating: all ten parameters 58/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 81 steps
  • 100Execution cost. Instruction body is 1618 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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)
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 227: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 81 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 3 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This debugging skill is not clearly malicious, but it gives agents broad autonomous authority to run commands, edit code, and collect sensitive browser artifacts with limited scoping.
LLM: suspicious (high) · 9 Jun 2026