Api endpoint probe

Skill: API Endpoint Probe

Purpose: Quick reconnaissance of API endpoint parameters before implementation — find what actually works (filters, pagination, limits, auth) via minimal test requests. When: Integrating with a new endpoint where unknown: which params it accepts, pagination type, whether it works without mandatory filters, actual response limit. Output: Table of "works / doesn't work" + recommended call pattern for implementation.

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PROCESS

Step 1 — Collect initial data

Ask user (if not in request):

1. URL or endpoint template (e.g. GET /v1/trades?market={id})
2. Is there auth — API key, Bearer token, cookie?
3. Goal: paginate all records / filter / one-time fetch?
4. Known params from docs? (even partial)

Step 2 — Build probe plan

Form minimal set of 3–5 test requests:

#	Goal	Params	Expected result
1	Base call, no filters	—	Does it work at all, response format
2	Page limit	limit=1 / size=1	Whether param exists, what it's called
3	Cursor pagination	cursor= / next= / after=	Pagination type
4	Time-based filter	startTs= / after= / since=	Whether timestamp filter works
5	Entity filter	market=X / user=Y	Is filter required or optional

Show plan to user — wait for "да" before executing.

Step 3 — Execute probe requests

For each request in plan:

1. Show exact request before executing
2. Execute via requests (Python) or curl — depending on environment
3. Record: status, response size, key fields

# Python probe template
import requests, json

BASE = "https://api.example.com"
HEADERS = {"Authorization": "Bearer TOKEN"}  # if auth needed

def probe(path, params=None):
    r = requests.get(BASE + path, headers=HEADERS, params=params)
    print(f"{r.status_code} | {len(r.content)}b | {path}?{r.request.path_url.split('?',1)[-1]}")
    try:
        data = r.json()
        if isinstance(data, list) and data:
            print(json.dumps(data[0], indent=2)[:300])
        elif isinstance(data, dict):
            print(json.dumps({k: type(v).__name__ for k, v in data.items()}))
    except:
        print(r.text[:200])
    return r

Step 4 — Record results

After all requests, output summary table:

── Probe results: [endpoint] ────────────────────────

| Parameter       | Works? | How to use                  |
|-----------------|--------|-----------------------------|
| no filters      | ✅/❌  | [observation]               |
| limit/size      | ✅/❌  | limit=N or size=N           |
| cursor paging   | ✅/❌  | next_cursor field in response|
| startTs filter  | ✅/❌  | startTs=unix_ms             |
| user filter     | ✅/❌  | required / optional         |

Recommended call for implementation:
  GET [path]?[param1=val]&[param2=val]
  Pagination: [cursor / offset / timestamp / none]
  Limit: [actual page limit]
  Notes: [what doesn't work or is unexpected]

Step 5 — Update documentation

If project has CLAUDE.md:

• Add findings to "Known Issues" or a separate "API Notes" section
• Note confirmed pagination type — to avoid re-checking

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RULES

• No more than 10 requests without explicit user consent
• Don't use mutating methods (POST/DELETE) without explicit instruction
• If endpoint returns 401/403 — report immediately, don't guess auth
• If param is undocumented but works — mark as "undocumented, verify in next API version"