Atlas / Skills / jeremylongshore / Klingai Debug Bundle

Klingai Debug BundleSAFE

skills/jeremylongshore/klingai-debug-bundle

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.18.0
Hosts
1 documented
License
MIT
Stars
2,824
01

Overview

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Read from source at commit 4f83675ca38aOBSERVED · 2026-10-09
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: klingai-debug-bundle
description: 'Set up logging and debugging for Kling AI API integrations. Use when
  troubleshooting video

  generation or building observability. Trigger with phrases like ''klingai debug'',
  ''kling ai logging'',

  ''klingai troubleshoot'', ''debug kling video generation''.

  '
allowed-tools: Read, Write, Edit, Bash(npm:*), Grep
version: 1.18.0
license: MIT
author: Jeremy Longshore <[email protected]>
tags:
- saas
- kling-ai
- debugging
- observability
compatibility: Designed for Claude Code
---
# Kling AI Debug Bundle

## Overview

Structured logging, request tracing, and diagnostic tools for Kling AI API integrations. Captures request/response pairs, task lifecycle events, and timing metrics for every call to `https://api.klingai.com/v1`.

## Debug-Enabled Client

```python
import jwt, time, os, requests, logging, json
from datetime import datetime

logging.basicConfig(
    level=logging.DEBUG,
    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
)
logger = logging.getLogger("kling.debug")

class KlingDebugClient:
    """Kling AI client with full request/response logging."""

    BASE = "https://api.klingai.com/v1"

    def __init__(self):
        self.ak = os.environ["KLING_ACCESS_KEY"]
        self.sk = os.environ["KLING_SECRET_KEY"]
        self._request_log = []

    def _get_headers(self):
        token = jwt.encode(
            {"iss": self.ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5},
            self.sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"}
        )
        return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

    def _traced_request(self, method, path, body=None):
        """Execute request with full tracing."""
        url = f"{self.BASE}{path}"
        start = time.monotonic()
        trace = {
            "timestamp": datetime.utcnow().isoformat(),
            "method": method,
            "path": path,
            "request_body": body,
        }

        try:
            if method == "POST":
                r = requests.post(url, headers=self._get_headers(), json=body, timeout=30)
            else:
                r = requests.get(url, headers=self._get_headers(), timeout=30)

            trace["status_code"] = r.status_code
            trace["response_body"] = r.json() if r.content else None
            trace["duration_ms"] = round((time.monotonic() - start) * 1000)

            logger.debug(f"{method} {path} -> {r.status_code} ({trace['duration_ms']}ms)")

            if r.status_code >= 400:
                logger.error(f"API error: {r.status_code} -- {r.text[:300]}")

            r.raise_for_status()
            return r.json()

        except Exception as e:
            trace["error"] = str(e)
            trace["duration_ms"] = round((time.monotonic() - start) * 1000)
            logger.exception(f"Request failed: {path}")
            raise
        finally:
            self._request_log.append(trace)

    def text_to_video(self, prompt, **kwargs):
        body = {
            "model_name": kwargs.get("model", "kling-v2-master"),
            "prompt": prompt,
            "duration": str(kwargs.get("duration", 5)),
            "mode": kwargs.get("mode", "standard"),
        }
        result = self._traced_request("POST", "/videos/text2video", body)
        task_id = result["data"]["task_id"]
        logger.info(f"Task created: {task_id}")
        return self._poll_with_logging("/videos/text2video", task_id)

    def _poll_with_logging(self, endpoint, task_id, max_attempts=120):
        start = time.monotonic()
        for attempt in range(max_attempts):
            time.sleep(10)
            result = self._traced_request("GET", f"{endpoint}/{task_id}")
            status = result["data"]["task_status"]
            elapsed = round(time.monotonic() - start)
            logger.info(f"Poll #{attempt + 1}: status={status}, elapsed={elapsed}s")

            if status == "succeed":
                logger.info(f"Task {task_id} completed in {elapsed}s")
                return result["data"]["task_result"]
            elif status == "failed":
                msg = result["data"].get("task_status_msg", "Unknown")
                logger.error(f"Task {task_id} failed after {elapsed}s: {msg}")
                raise RuntimeError(msg)

        raise TimeoutError(f"Task {task_id} timed out after {max_attempts * 10}s")

    def dump_log(self, filepath="kling_debug.json"):
        with open(filepath, "w") as f:
            json.dump(self._request_log, f, indent=2, default=str)
        logger.info(f"Debug log written to {filepath} ({len(self._request_log)} entries)")
```

## Usage

```python
client = KlingDebugClient()
try:
    result = client.text_to_video("A cat surfing ocean waves at sunset")
    print(f"Video: {result['videos'][0]['url']}")
except Exception:
    pass
finally:
    client.dump_log()  # always save debug log
```

## Structured Log Entry Format

```json
{
  "timestamp": "2026-03-22T10:30:00.000Z",
  "method": "POST",
  "path": "/videos/text2video",
  "request_body": {"model_name": "kling-v2-master", "prompt": "..."},
  "status_code": 200,
  "response_body": {"code": 0, "data": {"task_id": "abc123"}},
  "duration_ms": 342
}
```

## Quick Diagnostic Script

```bash
#!/bin/bash
# kling-diag.sh
echo "=== Kling AI Diagnostics ==="
echo "KLING_ACCESS_KEY: ${KLING_ACCESS_KEY:+set (${#KLING_ACCESS_KEY} chars)}"
echo "KLING_SECRET_KEY: ${KLING_SECRET_KEY:+set (${#KLING_SECRET_KEY} chars)}"

python3 -c "
import jwt, time, os, requests
ak = os.environ.get('KLING_ACCESS_KEY', '')
sk = os.environ.get('KLING_SECRET_KEY', '')
if not ak or not sk: print('ERROR: Missing credentials'); exit(1)
token = jwt.encode({'iss': ak, 'exp': int(time.time())+1800, 'nbf': int(time.time())-5},
                   sk, algorithm='HS256', headers={'alg':'HS256','typ':'JWT'})
r = requests.get('https://api.klingai.com/v1/videos/text2video',
                  headers={'Authorization': f'B
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-09 · audit v0.4.1 · source sha 4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__klingai-debug-bundle.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-094f83675ca38aSAFEB89first audit
06

Questions

What does the Klingai Debug Bundle skill do?

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Is Klingai Debug Bundle safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Klingai Debug Bundle access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Klingai Debug Bundle work with?

Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-09. The repository is watched, and a new audit runs when it changes — this is the first audit.

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