rest-graphql-debug

name	rest-graphql-debug
description	Diagnoses REST and GraphQL failures by isolating connectivity, TLS, auth, payload shape, parse, then semantics with curl and Python requests. Use when status or body is unexpected, auth fails, Postman works but code does not, or webhooks, pagination, or rate limits break. Not for UI rendering, SQL tuning, or DNS/firewall infrastructure; never hardcode API tokens in repro scripts.
version	1.2.1
license	MIT
metadata	{"hermes":{"tags":["api","rest","graphql","http","debugging","testing","curl","integration"],"category":"software-development","related_skills":["systematic-debugging","test-driven-development"]}}

API Testing & Debugging

Drive REST and GraphQL diagnosis through Hermes tools — terminal for curl, execute_code for Python requests, web_extract for vendor docs. Isolate the failing layer before guessing at the fix.

Windows host note: Primary shell is PowerShell. Use backtick (`) for line continuation instead of bash \, or keep curl commands on a single line. Use python (not python3) on Windows. Environment variables use $env:TOKEN in PowerShell or os.environ["TOKEN"] in Python.

When to Use

• API returns unexpected status or body
• Auth fails (401/403 after token refresh, OAuth, API key)
• Works in Postman but fails in code
• Webhook / callback integration debugging
• Building or reviewing API integration tests
• Rate limiting or pagination issues

Skip for: UI rendering, DB query tuning, or DNS/firewall infra (escalate).

Prerequisites

• curl available on PATH (bundled with Windows 10+ as curl.exe; verify with curl --version)
• Python 3.8+ with requests installed (pip install requests)
• API credentials available via environment variables — never hardcode tokens in scripts
• Optional: pytest for regression test templates (pip install pytest)

Procedure

Core Principle: Isolate the Layer, Then Fix

A 200 OK can hide broken data. A 500 can mask a one-character auth typo. Walk the chain in order; never skip a step.

1.   Connectivity   → can we reach the host at all?
1.5  Timeouts       → connect-slow vs read-slow?
2.   TLS/SSL        → cert valid and trusted?
3.   Auth           → credentials correct and unexpired?
4.   Request format → payload shape match server expectations?
5.   Response parse → does our code accept what came back?
6.   Semantics      → does the data mean what we assume?

Step 1 — Connectivity

terminal('nslookup api.example.com')
terminal('curl -v --connect-timeout 5 https://api.example.com/health')

Failures: DNS not resolving, firewall, VPN required, proxy missing.

Step 1.5 — Timeouts

Distinguish can't reach from reaches but slow:

terminal('curl -w "dns:%{time_namelookup}s connect:%{time_connect}s tls:%{time_appconnect}s ttfb:%{time_starttransfer}s total:%{time_total}s" -o NUL -s https://api.example.com/endpoint')

Windows note: Use -o NUL (not /dev/null) on PowerShell/cmd.

In Python, always pass a tuple timeout — requests has no default and will hang forever:

execute_code('''
import requests
from requests.exceptions import ConnectTimeout, ReadTimeout
try:
    requests.get(url, timeout=(3.05, 30))
except ConnectTimeout:
    print("Cannot reach host — DNS, firewall, VPN")
except ReadTimeout:
    print("Connected but server is slow")
''')

Diagnosis: high time_connect is network/firewall; high time_starttransfer with low time_connect is a slow server.

Step 2 — TLS/SSL

terminal('curl -vI https://api.example.com 2>&1 | Select-String "SSL|subject|expire|issuer"')

Failures: expired cert, self-signed, hostname mismatch, missing CA bundle. Use -k only for ad-hoc debug, never in code.

Step 3 — Authentication

# Token validity check
terminal('curl -s -o NUL -w "%{http_code}" -H "Authorization: Bearer $env:TOKEN" https://api.example.com/me')

Decode JWT exp claim — handles base64url padding correctly:

execute_code('''
import json, base64, os
tok = os.environ["TOKEN"]
payload = tok.split(".")[1]
payload += "=" * (-len(payload) % 4)
print(json.dumps(json.loads(base64.urlsafe_b64decode(payload)), indent=2))
''')

Checklist:

• Token expired? (exp claim in JWT)
• Right scheme? Bearer vs Basic vs Token vs X-Api-Key
• Right environment? Staging key on prod is a classic
• API key in header vs query param (?api_key=…)?

Step 4 — Request Format

terminal('curl -v -X POST https://api.example.com/endpoint -H "Content-Type: application/json" -d "{\"key\":\"value\"}" 2>&1')

Content-Type / body mismatch — the silent 415/400:

# WRONG — data= sends form-encoded, header lies
requests.post(url, data='{"k":"v"}', headers={"Content-Type": "application/json"})

# RIGHT — json= auto-sets header AND serializes
requests.post(url, json={"k": "v"})

# WRONG — Accept says XML, code calls .json()
requests.get(url, headers={"Accept": "text/xml"})

# RIGHT — let requests build multipart with boundary
requests.post(url, files={"file": open("doc.pdf", "rb")})

Common: form-encoded vs JSON, missing required fields, wrong HTTP method, unencoded query params.

Step 5 — Response Parsing

Always inspect content-type before calling .json():

execute_code('''
import requests
resp = requests.post(url, json=payload, timeout=10)
print(f"status={resp.status_code}")
print(f"headers={dict(resp.headers)}")
ct = resp.headers.get("Content-Type", "")
if "application/json" in ct:
    print(resp.json())
else:
    print(f"unexpected content-type {ct!r}, body={resp.text[:500]!r}")
''')

Failures: HTML error page where JSON expected, empty body, wrong charset.

Step 6 — Semantic Validation

Parsed cleanly — but is the data correct?

• Does "status": "active" mean what your code thinks?
• ID in response matches the one requested?
• Timestamps in expected timezone?
• Pagination returning all results, or just page 1?

GraphQL Quickstart

terminal('curl -X POST https://api.example.com/graphql -H "Content-Type: application/json" -H "Authorization: Bearer $env:TOKEN" -d "{\"query\":\"{ user(id: 1) { name email } }\"}"')

GraphQL gotcha: servers often return HTTP 200 even when the query failed. Always inspect the errors field regardless of status code:

execute_code('''
import os, requests
resp = requests.post(
    "https://api.example.com/graphql",
    json={"query": "{ user(id: 1) { name email } }"},
    headers={"Authorization": f"Bearer {os.environ['TOKEN']}"},
    timeout=10,
)
data = resp.json()
if data.get("errors"):
    for err in data["errors"]:
        print(f"GraphQL error: {err['message']} (path: {err.get('path')})")
print(data.get("data"))
''')

HTTP Status Playbook

401 Unauthorized — credentials missing or invalid:

1. Authorization header actually present? (curl -v to confirm)
2. Token correct and unexpired?
3. Right auth scheme? (Bearer vs Basic vs Token)
4. Some APIs use query param (?api_key=…) instead of header.

403 Forbidden — authenticated but not authorized:

1. Token has the required scopes/permissions?
2. Resource owned by a different account?
3. IP allowlist blocking you?
4. CORS in browser? (check Access-Control-Allow-Origin)

404 Not Found — resource doesn't exist or URL is wrong:

1. Path correct? (trailing slash, typo, version prefix)
2. Resource ID exists?
3. Right API version (/v1/ vs /v2/)?
4. Right base URL (staging vs prod)?

409 Conflict — state collision:

1. Resource already exists (duplicate create)?
2. Stale ETag / If-Match?
3. Concurrent modification by another process?

422 Unprocessable Entity — valid JSON, invalid data:

• Check error body for field names
• Field types (string vs int, date format)
• Required vs optional
• Enum values inside the allowed set

429 Too Many Requests — rate limited:

Check Retry-After and X-RateLimit-* headers. Exponential backoff:

execute_code('''
import time, requests

def with_backoff(method, url, **kwargs):
    for attempt in range(5):
        resp = requests.request(method, url, **kwargs)
        if resp.status_code != 429:
            return resp
        wait = int(resp.headers.get("Retry-After", 2 ** attempt))
        time.sleep(wait)
    return resp
''')

5xx — server-side, usually not your fault:

• 500 — server bug. Capture correlation ID, file with provider.
• 502 — upstream down. Backoff + retry.
• 503 — overloaded / maintenance. Check status page.
• 504 — upstream timeout. Reduce payload or raise timeout.

For all 5xx: backoff with jitter, alert on persistence.

Pagination & Idempotency

Pagination. Verify you're getting all results. Look for next_cursor, next_page, total_count. Two patterns:

• Offset (?limit=100&offset=200) — simple, can skip items if data shifts.
• Cursor (?cursor=abc123) — preferred for live or large datasets.

Idempotency. For non-idempotent operations (POST), send Idempotency-Key: <uuid> so retries don't double-charge / double-create. Mandatory for payments and orders.

Contract Validation

Catch schema drift before it hits production:

execute_code('''
import requests

def validate_user(data: dict) -> list[str]:
    errors = []
    required = {"id": int, "email": str, "created_at": str}
    for field, expected in required.items():
        if field not in data:
            errors.append(f"missing field: {field}")
        elif not isinstance(data[field], expected):
            errors.append(f"{field}: want {expected.__name__}, got {type(data[field]).__name__}")
    return errors

resp = requests.get(f"{BASE}/users/1", headers=HEADERS, timeout=10)
issues = validate_user(resp.json())
if issues:
    print(f"contract violations: {issues}")
''')

Run after API upgrades, when integrating new third parties, or in CI smoke tests.

Correlation IDs

Always capture the provider's request ID — fastest path to vendor support:

execute_code('''
import requests
resp = requests.post(url, json=payload, headers=headers, timeout=10)
request_id = (
    resp.headers.get("X-Request-Id")
    or resp.headers.get("X-Trace-Id")
    or resp.headers.get("CF-Ray")  # Cloudflare
)
if resp.status_code >= 400:
    print(f"failed status={resp.status_code} req_id={request_id} ts={resp.headers.get('Date')}")
''')

Vendor bug-report template:

Endpoint:    POST /api/v1/orders
Request ID:  req_abc123xyz
Timestamp:   2026-03-17T14:30:00Z
Status:      500
Expected:    201 with order object
Actual:      500 {"error":"internal server error"}
Repro:       curl -X POST … (auth: <REDACTED>)

Regression Test Template

Drop this into tests/ and run via terminal('python -m pytest tests/test_api_smoke.py -v'):

import os, requests, pytest

BASE_URL = os.environ.get("API_BASE_URL", "https://api.example.com")
TOKEN    = os.environ.get("API_TOKEN", "")
HEADERS  = {"Authorization": f"Bearer {TOKEN}"}

class TestAPISmoke:
    def test_health(self):
        resp = requests.get(f"{BASE_URL}/health", timeout=5)
        assert resp.status_code == 200

    def test_list_users_returns_array(self):
        resp = requests.get(f"{BASE_URL}/users", headers=HEADERS, timeout=10)
        assert resp.status_code == 200
        data = resp.json()
        assert isinstance(data.get("data", data), list)

    def test_get_user_required_fields(self):
        resp = requests.get(f"{BASE_URL}/users/1", headers=HEADERS, timeout=10)
        assert resp.status_code in (200, 404)
        if resp.status_code == 200:
            user = resp.json()
            assert "id" in user and "email" in user

     ():
        resp = requests.get(
            ,
            headers={: },
            timeout=,
        )
         resp.status_code == 

Hermes Tool Patterns

terminal — for curl, dig, openssl:

terminal('curl -sI https://api.example.com')
terminal('openssl s_client -connect api.example.com:443 -servername api.example.com < NUL 2>NUL | openssl x509 -noout -dates')

execute_code — for multi-step Python flows. When debugging spans auth → fetch → paginate → validate, use execute_code. Variables persist for the script, results print to stdout, no risk of token spam in your context:

execute_code('''
import os, requests

token = os.environ["API_TOKEN"]
base  = "https://api.example.com"
H     = {"Authorization": f"Bearer {token}"}

# 1. auth
me = requests.get(f"{base}/me", headers=H, timeout=10)
print(f"auth {me.status_code}")

# 2. paginate
all_users, cursor = [], None
while True:
    params = {"cursor": cursor} if cursor else {}
    r = requests.get(f"{base}/users", headers=H, params=params, timeout=10)
    body = r.json()
    all_users.extend(body["data"])
    cursor = body.get("next_cursor")
    if not cursor:
        break
print(f"users={len(all_users)}")
''')

web_extract — for vendor API docs. Pull the spec for the endpoint you're debugging instead of guessing:

web_extract(urls=["https://docs.example.com/api/v1/users"])

delegate_task — for full CRUD test sweeps:

delegate_task(
    goal="Test all CRUD endpoints for /api/v1/users",
    context="""
Follow the rest-graphql-debug skill.
Base URL: https://api.example.com
Auth: Bearer token from API_TOKEN env var.

For each verb (POST, GET, PATCH, DELETE):
  - happy path: assert status + response schema
  - error cases: 400, 404, 422
  - log a repro curl for any failure (redact tokens)

Output: pass/fail per endpoint + correlation IDs for failures.
""",
    toolsets=["terminal", "file"],
)

Vendor docs

This skill does not ship a companion pack. Use the sections above, then pull vendor docs directly:

• GraphQL schema/field issues — GraphQL Quickstart (introspection query in that section)
• OAuth/OIDC token exchange — Step 3 Authentication
• Vendor cursor formats — Pagination & Idempotency, then the vendor's pagination docs

Output Format

When reporting findings, use this structure:

## Finding
Endpoint: POST /api/v1/users
Status:   422 Unprocessable Entity
Req ID:   req_abc123xyz

## Repro
curl -X POST https://api.example.com/api/v1/users `
  -H 'Content-Type: application/json' `
  -H 'Authorization: Bearer <REDACTED>' `
  -d '{"name":"test"}'

## Root Cause
Missing required field `email`. Server validation rejects before processing.

## Fix
-d '{"name":"test","email":"[e-mail]"}'

Pitfalls

• GraphQL returns 200 on errors. Always check the errors array in the response body, not just the HTTP status code.
• requests has no default timeout. Without timeout=(connect, read) it will hang forever. Always pass a tuple.
• data= vs json= in requests. data='{"k":"v"}' with a JSON Content-Type header sends form-encoded data with a lying header. Use json={"k":"v"} to auto-set header and serialize correctly.
• Staging key on prod. Classic mistake — verify the environment matches the token.
• Credentials in URLs. API keys in query strings end up in server logs, browser history, referrer headers. Use headers instead.
• -k flag in production code. Only for ad-hoc debug. Never ship code that skips TLS verification.
• Windows path differences. Use NUL not /dev/null, python not python3, backtick ` not backslash \ for line continuation in PowerShell.
• Offset pagination skipping items. If data shifts between page fetches, offset pagination can skip or duplicate items. Use cursor pagination for live data.
• Missing Idempotency-Key on retries. POST retries without an idempotency key can double-charge or double-create. Mandatory for payments and orders.
• Token leaks in logs. Never log full tokens. Redact: Bearer <REDACTED>. Rotate immediately if a token surfaces in logs, error messages, or git history.

Security Leak Checklist

• Credentials in URLs — API keys in query strings leak to server logs, browser history, referrer headers. Use headers.
• PII in error responses — 404 on /users/123 shouldn't reveal whether the user exists (enumeration).
• Stack traces in prod — 500s shouldn't leak file paths, framework versions.
• Internal hostnames/IPs — 10.x.x.x, internal-api.corp.local in error bodies.
• Tokens echoed back — Some APIs include the auth token in error details. Verify they don't.
• Verbose Server / X-Powered-By — Stack-info leaks. Note for security review.

Safe Logging Helper

def redact_auth(headers: dict) -> dict:
    sensitive = {"authorization", "x-api-key", "cookie", "set-cookie"}
    return {k: ("<REDACTED>" if k.lower() in sensitive else v) for k, v in headers.items()}

Verification

1. Connectivity verified:

   terminal('curl -sI https://api.example.com/health')
   

   Expected: HTTP/... 200 or HTTP/... 204 in output.

2. Auth verified:

   terminal('curl -s -o NUL -w "%{http_code}" -H "Authorization: Bearer $env:TOKEN" https://api.example.com/me')
   

   Expected: 200 (not 401 or 403).

3. Response parses as JSON:

   execute_code('''
   import requests
   resp = requests.get("https://api.example.com/users/1", headers={"Authorization": "Bearer <TOKEN>"}, timeout=10)
   ct = resp.headers.get("Content-Type", "")
   assert "application/json" in ct, f"unexpected content-type: {ct}"
   data = resp.json()
   assert "id" in data, "missing required field: id"
   print(f"OK: status={resp.status_code}, fields={list(data.keys())}")
   ''')
   

   Expected: OK: status=200, fields=[...]

4. Regression tests pass:

   terminal('python -m pytest tests/test_api_smoke.py -v')
   

   Expected: all tests PASSED.

5. No token leaks in output:

   execute_code('''
   import re
   # Scan recent output for token patterns
   token_pattern = re.compile(r"Bearer [A-Za-z0-9._-]{20,}")
   # If any output matches, rotate token immediately
   print("Scan complete — verify no raw tokens in logs")
   ''')
   

Related

• systematic-debugging — once the failing API layer is isolated, root-cause your code
• test-driven-development — write the regression test before shipping the fix