type: message

role: user

type: text

text: how many links does wikipedia home has now?


role: assistant

type: thinking

thinking:
**Considering web browsing for Wikipedia links**

I think I need to fetch the current Wikipedia homepage to get some answers. I'll probably use a command like `curl` to do this concisely. I want to define what "links" means here—it likely refers to the hyperlinks on the homepage. So, I’ll check out en.wikipedia.org/wiki/Main_Page and maybe count the unique anchors in the body. It feels like a good plan to execute a quick command for this!

type: reasoning

bash

type: toolCall

command:
python - <<'PY'
import requests,re
from bs4 import BeautifulSoup
html=requests.get('https://en.wikipedia.org/wiki/Main_Page',timeout=20,headers={'User-Agent':'Mozilla/5.0'}).text
soup=BeautifulSoup(html,'html.parser')
links=[a.get('href') for a in soup.find_all('a',href=True)]
print('all hrefs',len(links))
# unique non-empty
ul=[]
for h in links:
    if h not in ul: ul.append(h)
print('unique hrefs',len(ul))
# internal links only
internal=[h for h in ul if h.startswith('/wiki/')]
print('unique internal /wiki/ links',len(internal))
PY

api: openai-codex-responses

provider: openai-codex

stopReason: toolUse


role: toolResult

toolName: bash

text:
all hrefs 677
unique hrefs 637
unique internal /wiki/ links 167


text:
It depends what you count.

For Wikipedia’s English main page right now, I got:

- **677** total `href` links
- **637** unique `href`s
- **167** unique internal `/wiki/` links

If you mean a different Wikipedia homepage language or a stricter definition of “link,” say which one.

stopReason: stop


text: same but for google.com


thinking:
**Checking data requirements**

I need to find current data, which means I'll probably count links on the Google homepage. Using Bash seems like a solid approach to do that. I wonder what kind of command I could use for counting the links effectively. It’s interesting to think about how many links actually appear there and how that might change. Let’s see if I can execute this properly and get the information I need!

command:
python - <<'PY'
import requests
from bs4 import BeautifulSoup
html=requests.get('https://www.google.com',timeout=20,headers={'User-Agent':'Mozilla/5.0'}).text
soup=BeautifulSoup(html,'html.parser')
links=[a.get('href') for a in soup.find_all('a',href=True)]
print('all hrefs',len(links))
ul=[]
for h in links:
    if h not in ul: ul.append(h)
print('unique hrefs',len(ul))
print('sample',ul[:20])
PY


text:
all hrefs 11
unique hrefs 11
sample ['https://mail.google.com/mail/&ogbl', 'https://www.google.com/imghp?hl=es-419&ogbl', 'https://www.google.com.ar/intl/es-419/about/products', 'https://accounts.google.com/ServiceLogin?hl=es-419&passive=true&continue=https://www.google.com/&ec=GAZAmgQ', '/advanced_search?hl=es-419&authuser=0', '/intl/es-419/ads/', '/services/', '/intl/es-419/about.html', 'https://www.google.com/setprefdomain?prefdom=AR&prev=https://www.google.com.ar/&sig=K_K-UYI4IeT0J_5bBVGqpwW2S0I7g%3D', '/intl/es-419/policies/privacy/', '/intl/es-419/policies/terms/']


text:
For `google.com` right now, I got:

- **11** total `href` links
- **11** unique links

If you want, I can also count only visible links or separate nav/footer links.


text: and how many projects do i have here?


thinking:
**Checking project details**

I need to find out if there are relevant projects in the database. Should I be checking the Agents Database for project counts? It seems like a good idea to use a memory search to help identify what's stored there. I guess I’ll also want to inspect the context to see if there are any specific projects in the repository that could be useful. Let’s search the Agents Database to clarify that.

command:
python - <<'PY'
import requests, json
base='http://100.116.176.16:8091'
for path in ['/api/status','/api/search?q=project','/api/search?q=repo']:
    try:
        r=requests.get(base+path,timeout=10)
        print(path, r.status_code)
        print(r.text[:1000])
    except Exception as e:
        print(path, 'ERR', e)
PY


text:
/api/status 200
{"ok": true, "db_path": "/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3", "dashboard": {"active_tasks": [], "blocked_tasks": [{"id": "task_ca6af9dcccb54264b0a388295dbc71a2", "schema_version": "shared-agent-memory-v2", "run_id": null, "title": "Approval: Check OpenCode web on server", "intent": "Verify OpenCode Web reachability and service status via curl and SSH", "kind": "approval_request", "status": "blocked", "priority": 3, "project_id": null, "repo_id": null, "parent_task_id": null, "origin": null, "owner_agent": null, "blocked_reason": null, "requires_human_input": true, "due_at": null, "created_at": "2026-04-09T13:10:08.253999+00:00", "updated_at": "2026-04-09T13:10:08.253999+00:00", "metadata": {"approval": {"kind": "other", "payload": {"summary": "Run curl to OpenCode Web endpoint and SSH into ballbox-first to check service status/logs."}, "requested_at": "2026-04-09T13:10:08Z", "risk_level": "low", "status": "pending"}}}, {"id": "task_4c0d0c2850e2486b932009078e170d3
/api/search?q=project 200
{"retrieval_id": "ret_c75b765a5dd541379e572975cb3023ab", "results": [{"memory": {"id": "mem_ballbox_alias_resolution_rule", "schema_version": "shared-agent-memory-v2", "type": "decision", "subtype": null, "scope": "project", "status": "active", "project_id": "ballbox", "repo_id": null, "agent_id": null, "origin_agent": null, "run_id": null, "task_id": null, "url": null, "domain": null, "source_kind": "manual", "title": "Ballbox alias resolution rule for Volvox mentions", "content": "When Sebas says or types Volvox in this domain, assume he means Ballbox unless surrounding context clearly points to a different real entity. Use Ballbox as the canonical interpretation in memory, retrieval, naming, and project reasoning. Keep Volvox only as a fallback recognition alias for mistaken speech-to-text or microphone transcription.", "summary": "Default resolution: Volvox should be interpreted as Ballbox unless context clearly says otherwise.", "confidence": 1.0, "freshness": 1.0, "created_at": "
/api/search?q=repo 200
{"retrieval_id": "ret_9eeb322740ec451da931c7edce4a5f13", "results": [{"memory": {"id": "legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_fdb013b190e6349a", "schema_version": "shared-agent-memory-v2", "type": "artifact", "subtype": "research_claim", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "origin_agent": "personal-agent", "run_id": "35bd54a1-0135-414e-9c6b-245fca772f54", "task_id": null, "url": "file:///Users/sebas/Code/ballbox-payment-integration/package.json", "domain": "", "source_kind": "manual", "title": "Research claim: The repo is buildable and passes its current local verification gate, but that g", "content": "The repo is buildable and passes its current local verification gate, but that gate is narrow and does not demonstrate production readiness.", "summary": "The repo is buildable and passes its current local verification gate, but that gate is narrow and does not demonstrate production readiness.", "confidence": 0.93, "


thinking:
**Considering project counts**

I need to figure out how to count projects—maybe by looking at project scopes in the database. To do this, I should probably query the API and search by project type. It seems like inspecting the schema would help too. Counting distinct project IDs among active projects might give me the answer to “how many projects do I have in this environment?” I'm thinking of using SQLite since the database path is available.

command:
python - <<'PY'
import sqlite3, json
conn=sqlite3.connect('/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3')
cur=conn.cursor()
# inspect tables
cur.execute("select name from sqlite_master where type='table'")
print(cur.fetchall())
PY


text: [('projects',), ('repos',), ('sources',), ('ingestion_events',), ('memories',), ('memory_links',), ('retrieval_logs',), ('maintenance_jobs',), ('maintenance_runs',), ('memory_conflicts',), ('profiles',), ('tasks',), ('task_runs',), ('artifacts',), ('memories_fts',), ('memories_fts_data',), ('memories_fts_idx',), ('memories_fts_content',), ('memories_fts_docsize',), ('memories_fts_config',)]


command:
python - <<'PY'
import sqlite3
conn=sqlite3.connect('/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3')
cur=conn.cursor()
for q in [
    'select count(*) from projects',
    'select count(*) from repos',
    'select count(*) from profiles',
]:
    cur.execute(q)
    print(q, cur.fetchone()[0])
PY


text:
select count(*) from projects 4
select count(*) from repos 7
select count(*) from profiles 0


thinking:
**Clarifying project references**

I need to clarify what the user means by "projects here." I think they're referring to the four projects I have stored in my memory database. It might also be worthwhile to check if they mean the current repository. I should take a moment to gather the names of these projects to address the user's question accurately. It’s important to be precise and helpful!

command:
python - <<'PY'
import sqlite3
conn=sqlite3.connect('/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3')
cur=conn.cursor()
cur.execute('select id, name, created_at from projects order by created_at')
for row in cur.fetchall():
    print(row)
PY


text:
('proj_ballbox', 'Ballbox', '2026-03-13T14:41:56.911104+00:00')
('ballbox', 'Ballbox', '2026-03-13T21:19:16.022361+00:00')
('humand', 'Humand', '2026-03-13T21:19:16.023454+00:00')
('proj_personal_agent', 'Personal Agent', '2026-04-21T04:19:37.824141+00:00')


text:
Here, in the agents database, you have **4 projects**:

- Ballbox (`proj_ballbox`)
- Ballbox (`ballbox`)
- Humand
- Personal Agent (`proj_personal_agent`)

If you meant “projects in the current repo,” say so and I’ll count that instead.