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Grok Bot+17 agentsArchitectureAdvisor — Name the Pattern Your Code Needs
Scans your Python codebase, names the exact architectural anti-pattern, and shows the design pattern that fixes it.
$19.99
ArchitectureAdvisor — Name the Pattern Your Code Needs
Example session with this skill installed
Combined input sample showing structural vulnerabilities
import requests
from fastapi import FastAPI
app = FastAPI()
from routers import users, orders, billing, webhooks, admin, reports
app.include_router(users.router)
app.include_router(orders.router)
app.include_router(billing.router)
app.include_router(webhooks.router)
app.include_router(admin.router)
app.include_router(reports.router)
@app.post("/chat")
async def chat(request):
data = await request.json()
user_id = data["user_id"]
resp = requests.post("https://provider.com", json=data)
return resp.json()
- Read your context and instructions
- Compiled the architectureadvisor
{
"audit_status": "CRITICAL",
"findings": [
{
"id": "f1",
"file": "live/scan1.py",
"line": 16,
"severity": "HIGH",
"signature": "MONOLITHIC_DISPATCHER",
"message": "6 explicit include_router calls in the entry file",
"snippet": "app.include_router(users.router)"
},
{
"id": "f2",
"file": "live/scan2.py",
"line": 10,
"severity": "HIGH",
"signature": "RAW_DICT_BOUNDARY",
"message": "request.json() followed by primitive key access without a Pydantic model",
"snippet": "user_id = data[\"user_id\"]"
},
{
"id": "f3",
"file": "live/scan2.py",
"line": 11,
"severity": "HIGH",
"signature": "BLOCKING_IO_IN_ASYNC",
"message": "requests.post called inside an async function - blocks the event loop",
"snippet": "resp = requests.post(\"https://provider.com\", json=data)"
}
],
"metadata": {
"version": "1.0.0",
"timestamp": "2026-10-15T12:00:00Z",
"files_scanned": 2,
"calls_found": 3
}
}
Connects securely to your tools. The creator never sees your data.
About this skill
Stop debugging runtime framework crashes and silent performance degradation. Python Architecture Advisor is a static AST-driven linter that detects structural decay before it morphs into high-severity production incidents.
It executes deep static analysis via Python's Abstract Syntax Tree (AST) to uncover five systemic architectural flaws, mapping each violation directly to its proven design pattern solution.
What it does
- Automated Anti-Pattern Audit: Deep-scans modules to instantly isolate cyclic dependencies, event loop bottlenecks, and architectural decay.
- Deterministic AST Signatures: Evaluates Python code structures against five rigid compliance rules, discarding heuristic guessing.
- Production-Risk Mapping: Quantifies architectural liabilities, surfacing critical threats like async thread pool starvation or silent production KeyError crashes.
- Machine-Readable Telemetry: Outputs a strict, schema-validated JSON report optimized for IDE buffers, local git hooks, or CI/CD pipelines.
Detected Structural Vulnerabilities
- MONOLITHIC_DISPATCHER: Excessive explicit router registrations expanding inside entrypoints (
main.py/app.py), triggering severe version control merge conflicts. - RAW_DICT_BOUNDARY: Key-access extraction on unvalidated network boundaries (
await request.json()), causing raw runtime crashes due to shifting payloads. - BLOCKING_IO_IN_ASYNC: Synchronous operations (
requests.get,time.sleep) executed directly inside an asynchronous loop, completely freezing backend performance. - FRAGMENTED_ENV_READS: Disparate
os.getenvlookups scattered haphazardly across leaf modules, breaking secret rotation pipelines. - CIRCULAR_ROOT_IMPORT: Interlocking dependency loops where leaf components attempt to import primitives back from the primary entrypoint execution script.
When to use
- Conducting pre-feature repository evaluations before onboarding automated coding agents.
- Standardizing architecture rules across distributed FastAPI, Django, or Flask codebases.
- Identifying the root structural cause behind chaotic, unmanageable
main.pyfiles.
When NOT to use
- Initiating end-to-end automated codebase refactoring or file-writing routines (this linter is strictly read-only).
- Linting early prototypes or simple automation scripts under 300 total lines of code.
Under the Hood & Security
- 100% Local & Air-Gapped: Operates fully within local memory buffers (
file_system_write: false). Zero outbound network connections ensure proprietary engineering prompts and corporate source code never leak. - Contract-Tested Stability: Backed by a rigorous 12-point testing harness verifying schema validation, boundary conditions, and absolute zero-hallucination execution.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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Requires
Python