SKILLEMALL.ai

BF code-exploration

Exhaustive repository exploration procedure — Glob the whole tree into a written inventory, group it by directory, and account for every file including templates, Dockerfiles, compose and k8s manifests, nginx/uwsgi/gunicorn config, CI workflows, dotfiles, SQL migrations, static assets and __init__.py. Load FIRST, before any lens, when you are asked to map a repository, enumerate its attack surface, find entry points, decide what is in scope, or conclude that something is absent. Covers reading paginated files to the last line, following handler-to-template and handler-to-model edges with GraphImporters / GraphNeighbors, and reporting coverage gaps honestly.

visa/visa-vulnerability-agentic-harness Agent Skills author: visa 2 files · 1 script body ≈ 4 183 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Exhaustive repository exploration procedure — Glob the whole tree into a written inventory, group it by directory, and account for every file including…

As a process F 34/100 · No process to follow — References files that are not bundled: assets/**

ProcedureKubernetesDockerSoftware developmentInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
34/100
No process to follow
References files that are not bundled: assets/**
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/**

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: assets/**
  • 0Tools and files. 1 referenced file(s) missing: assets/**
  • 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
  • 30Running it twice. 7 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 4183 tokens
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 665: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.