SKILLEMALL.ai

BC application-security-testing

Application security testing (AppSec) across a whole product with Strix — decide which asset needs which test (source code, running web app, API, CI pipeline), run it, and turn the results into a ranked remediation plan. Autonomous agents exploit and prove each issue instead of emitting static-analysis alerts, so the plan is ordered by what is actually reachable. Use when the user asks for an application security review or audit, an appsec assessment, vulnerability scanning across their stack, a security review before a launch or a customer security questionnaire, or does not yet know which kind of security test they need.

usestrix/strix Agent Skills author: usestrix Apache-2.0 1 file body ≈ 943 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Application security testing (AppSec) across a whole product with Strix — decide which asset needs which test (source code, running web app, API, CI…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureSoftware developmentInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
96
Quality 40%
81
Run on models
none yet
Process rating
C
57/100
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

    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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Risky intent intent-offensive-security SKILL.md:14
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      Install, LLM setup, all CLI flags, and the managed-cloud path live in the **penetration-testing-with-strix** skill. Read it first if `strix --version` fails. For a run with no Docker and no LLM key, t
      detector
    • low Risky intent intent-offensive-security SKILL.md:39
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | No Docker, no LLM key, or a report an auditor will accept | **managed-pentesting-with-strix** |
    • low Risky intent intent-offensive-security SKILL.md:46
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      2. Pentest staging with credentials, and pass the repo as a second target so the agents keep source context.
    • low Risky intent intent-offensive-security SKILL.md:60
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Deduplicate: the same root cause often surfaces in both the code review and the live pentest.

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 57/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 943 tokens

    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
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 630: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 12 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.