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docs: update poller dispatcher, PR state machine, agent chaining (closes #7) #8

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248
AUTOMATED_DEV.md
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@ -74,103 +74,108 @@ back to issues.
### PR State Machine
Once a PR exists, it enters a finite state machine tracked by Gitea labels and
issue assignments. Labels represent the current state; the assignment field
represents who's responsible for the next action.
Once a PR exists, it enters a finite state machine tracked by Gitea labels. Each
PR has exactly one state label at a time, plus a `bot` label indicating it's the
agent's turn to act.
#### States (Gitea Labels)
| Label | Color | Meaning |
| -------------- | ------ | ------------------------------------------------- |
| `needs-rebase` | red | PR has merge conflicts or is behind main |
| `needs-checks` | orange | `make check` does not pass cleanly |
| `needs-review` | yellow | Code review not yet done |
| `needs-rework` | purple | Code review found issues that need fixing |
| `merge-ready` | green | All checks pass, reviewed, rebased, conflict-free |
| Label | Color | Meaning |
| -------------- | ------ | --------------------------------------------- |
| `needs-review` | yellow | Code pushed, `docker build .` passes, awaiting review |
| `needs-rework` | purple | Code review found issues that need fixing |
| `merge-ready` | green | Reviewed clean, build passes, ready for human |
#### Transitions
Earlier iterations included `needs-rebase` and `needs-checks` states, but we
eliminated them. Rebasing is handled inline by workers and reviewers (they
rebase onto the target branch as part of their normal work). And `docker build .`
is the only check — it's run by workers before pushing and by reviewers before
approving. There's no separate "checks" phase.
#### The `bot` Label + Assignment Model
The `bot` label signals that an issue or PR is the agent's turn to act. The
assignment field tracks who is actively working on it:
- **`bot` label + unassigned** = work available, poller dispatches an agent
- **`bot` label + assigned to agent** = actively being worked
- **No `bot` label** = not the agent's turn (either human's turn or done)
The notification poller assigns the agent account to the issue at dispatch time,
before the agent session even starts. This prevents race conditions — by the
time a second poller scan runs, the issue is already assigned and gets skipped.
When the agent finishes its step and spawns the next agent, it unassigns itself
first (releasing the lock). The next agent's first action is to verify it's the
only one working on the issue by checking comments for duplicate work.
At chain-end (`merge-ready`): the agent assigns the human and removes the `bot`
label. The human's PR inbox contains only PRs that are genuinely ready to merge.
#### Agent Chaining — No Self-Review
Each step in the pipeline is handled by a separate, isolated agent session.
Agents spawn the next agent in the chain via `openclaw cron add --session
isolated`. This enforces a critical rule: **the agent that wrote the code never
reviews it.**
The chain looks like this:
```
New PR created
│
▼
[needs-rebase] ──rebase onto main──▶ [needs-checks]
▲ │
│ run make check
│ (main updated, │
│ conflicts) ┌─────────────┴──────────────┐
│ │ │
│ passes fails
│ │ │
│ ▼ ▼
│ [needs-review] [needs-checks]
│ │ (fix code, re-run)
│ code review
│ │
│ ┌─────────┴──────────┐
│ │ │
│ approved issues found
│ │ │
│ ▼ ▼
│ [merge-ready] [needs-rework]
│ │ │
│ assign human fix issues
│ │
│ ▼
└───────────────────────────── [needs-rebase]
(restart cycle)
Worker agent (writes/fixes code)
→ docker build . → push → label needs-review
→ unassign self → spawn reviewer agent → STOP
Reviewer agent (reviews code it didn't write)
→ read diff + referenced issues → review
→ PASS: rebase if needed → docker build . → label merge-ready
→ assign human → remove bot label → STOP
→ FAIL: comment findings → label needs-rework
→ unassign self → spawn worker agent → STOP
```
The cycle can repeat multiple times: rebase → check → review → rework → rebase →
check → review → rework → ... until the PR is clean. Each iteration typically
addresses a smaller set of issues until everything converges.
The cycle repeats (worker → reviewer → worker → reviewer → ...) until the
reviewer approves. Each agent is a fresh session with no memory of previous
iterations — it reads the issue comments and PR diff to understand context.
#### Assignment Rules
#### TOCTOU Protection
- **PR in any state except `merge-ready`** → assigned to the agent. It's the
agent's job to drive it forward through the state machine.
- **PR reaches `merge-ready`** → assigned to the human. This is the ONLY time a
PR should land in the human's queue.
- **Human requests changes during review** → PR moves back to `needs-rework`,
reassigned to agent.
Just before changing labels or assignments, agents re-read all comments and
current labels via the API. If the state changed since they started (another
agent already acted), they report the conflict and stop. This prevents stale
agents from overwriting fresh state.
This means the human's PR inbox contains only PRs that are genuinely ready to
merge — no half-finished work, no failing CI, no merge conflicts. Everything
else is the agent's problem.
#### Race Detection
If an agent starts and finds its work was already done (e.g., a reviewer sees a
review was already posted, or a worker sees a PR was already created), it
reports to the status channel and stops.
#### The Loop in Practice
A typical PR might go through this cycle:
A typical PR goes through this cycle:
1. Agent creates PR, labels `needs-rebase`
2. Agent rebases onto main → labels `needs-checks`
3. Agent runs `make check` — lint fails → fixes lint, pushes → back to
`needs-rebase` (new commit)
4. Agent rebases → `needs-checks` → runs checks → passes → `needs-review`
5. Agent does code review — finds a missing error check → `needs-rework`
6. Agent fixes the error check, pushes → `needs-rebase`
7. Agent rebases → `needs-checks` → passes → `needs-review`
8. Agent reviews — looks good → `merge-ready`
9. Agent assigns to human
10. Human reviews, merges
1. Worker agent creates PR, runs `docker build .`, labels `needs-review`
2. Worker spawns reviewer agent
3. Reviewer reads diff — finds a missing error check → labels `needs-rework`
4. Reviewer spawns worker agent
5. Worker fixes the error check, rebases, runs `docker build .`, labels
`needs-review`
6. Worker spawns reviewer agent
7. Reviewer reads diff — looks good → rebases → `docker build .` → labels
`merge-ready`, assigns human
8. Human reviews, merges
Steps 1-9 happen without human involvement. The human sees a clean, reviewed,
passing PR ready for a final look.
Steps 1-7 happen without human involvement. Each step is a separate agent
session that spawns the next one.
#### Automated Sweep
#### Safety Net
A periodic cron job (every 4 hours) scans all open PRs across all repos:
- **No label** → classify into the correct state
- **`needs-rebase`** → spawn agent to rebase
- **`needs-checks`** → spawn agent to run checks and fix failures
- **`needs-review`** → spawn agent to do code review
- **`needs-rework`** → spawn agent to fix review feedback
- **`merge-ready`** → verify still true (main may have updated since), ensure
assigned to human
This catches PRs that fell through the cracks — an agent session that timed out
mid-rework, a rebase that became necessary when main moved forward, etc.
The notification poller runs a periodic scan (every 2 minutes) of all watched
repos for issues/PRs with the `bot` label that are unassigned. This catches
broken chains — if an agent crashes or times out without spawning the next agent,
the poller will eventually re-dispatch. A 30-minute cooldown prevents duplicate
dispatches during normal operation.
#### Why Labels + Assignments
@ -263,26 +268,45 @@ A practical setup:
- **DM with agent** — Private conversation, sitreps, sensitive commands
- **Project-specific channels** — For coordination with external collaborators
### The Notification Poller
### The Notification Poller + Dispatcher
Because the agent can't see Gitea webhooks in Mattermost (bot-to-bot visibility
issue), we built a lightweight Python script that polls the Gitea notifications
API every 2 seconds and wakes the agent via OpenClaw's `/hooks/wake` endpoint
when new notifications arrive.
issue), we built a Python script that both polls and dispatches. It polls the
Gitea notifications API every 15 seconds, triages each notification (checking
@-mentions and assignment), marks them as read, and spawns one isolated agent
session per actionable item via `openclaw cron add --session isolated`.
The poller also runs a secondary **label scan** every 2 minutes, checking all
watched repos for open issues/PRs with the `bot` label that are unassigned
(meaning they need work but no agent has claimed them yet). This catches cases
where the agent chain broke — an agent timed out or crashed without spawning the
next one.
Key design decisions:
- **The poller never marks notifications as read.** That's the agent's job after
processing. Prevents the poller and agent from racing.
- **Tracks notification IDs, not counts.** Only fires on genuinely new
notifications, not re-reads of existing ones.
- **The wake message tells the agent to route output to Gitea/Mattermost, not
DM.** Prevents chatty notification processing from disturbing the human.
- **Zero dependencies.** Python stdlib only (`urllib`, `json`, `time`). Runs
anywhere.
- **The poller IS the dispatcher.** No flag files, no heartbeat dependency. The
poller triages notifications and spawns agents directly.
- **Marks notifications as read immediately.** Prevents re-dispatch on the next
poll cycle.
- **Assigns the agent account at dispatch time.** Before spawning the agent
session, the poller assigns the bot user to the issue via API. This prevents
race conditions — subsequent scans skip assigned issues.
- **Dispatched issues are tracked in a persistent JSON file.** Survives poller
restarts. Entries auto-prune after 1 hour.
- **30-minute re-dispatch cooldown.** The poller won't re-dispatch for the same
issue within 30 minutes, even if it appears unassigned again.
- **Concurrency cap.** The poller checks how many agents are currently running
and defers dispatch if the cap is reached.
- **Stale agent reaper.** Kills agent sessions that have been running longer
than 10 minutes (the `--timeout-seconds` flag isn't always enforced).
- **`bot` label + `merge-ready` skip.** The label scan skips issues that are
already labeled `merge-ready` — those are in the human's court.
- **Zero dependencies.** Python stdlib only. Runs anywhere.
Response time: ~15-30 seconds from notification to agent starting work.
Full source code is available in
[OPENCLAW_TRICKS.md](OPENCLAW_TRICKS.md#the-gitea-notification-poller).
[OPENCLAW_TRICKS.md](OPENCLAW_TRICKS.md#gitea-integration--notification-polling).
## CI: Gitea Actions
@ -371,42 +395,34 @@ Everything gets a production URL with automatic TLS via Traefik.
Putting it all together, the development lifecycle looks like this:
```
1. Issue filed in Gitea (by human or agent)
1. Human labels issue with `bot` (or agent files issue)
↓
2. Agent picks up the issue (via notification poller)
2. Poller detects `bot` label + unassigned → assigns agent → spawns worker
↓
3. Agent posts "starting work on #N" to Mattermost #git
3. Worker agent clones repo, writes code, runs `docker build .`
↓
4. Agent (or sub-agent) creates branch, writes code, pushes
4. Worker creates PR "(closes #N)", labels `needs-review`
↓
5. Gitea webhook fires → #git shows the push
5. Worker spawns reviewer agent → stops
↓
6. CI runs docker build → passes or fails
6. Reviewer agent reads diff + referenced issues → reviews
↓
7. Agent creates PR "(closes #N)"
7a. Review PASS → reviewer rebases if needed → `docker build .`
→ labels `merge-ready` → assigns human → removes `bot`
↓
8. Gitea webhook fires → #git shows the PR
7b. Review FAIL → reviewer labels `needs-rework`
→ spawns worker agent → back to step 3
↓
9. Agent reviews code, runs make check locally, verifies
8. Human reviews, merges
↓
10. Agent assigns PR to human when all checks pass
9. Gitea webhook fires → µPaaS deploys to production
↓
11. Human reviews, requests changes or approves
↓
12. If changes requested → agent reworks, back to step 6
↓
13. Human merges PR
↓
14. Gitea webhook fires → µPaaS deploys to production
↓
15. Gitea webhook fires → #git shows the merge
↓
16. Site/service is live on production URL
10. Site/service is live
```
Steps 2-10 can happen without any human involvement. The human's role is reduced
to: review the PR, approve or request changes, merge. Everything else is
automated.
Steps 2-7 happen without any human involvement, driven by agent-to-agent
chaining. The human's role is reduced to: label the issue, review the final PR,
merge. Everything else is automated.
### Observability

366
OPENCLAW_TRICKS.md
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@ -197,33 +197,46 @@ OpenClaw runs on a Mac Studio on a home LAN.
The solution: a Python script that both polls and dispatches. It polls the Gitea
notifications API every 15 seconds, triages each notification (checking
assignment and @-mentions), marks them as read, and spawns one isolated agent
@-mentions and assignments), marks them as read, and spawns one isolated agent
session per actionable item via `openclaw cron add --session isolated`.
The poller also runs a secondary **assignment scan** every 2 minutes, checking
all watched repos for open issues/PRs assigned to the bot that were recently
updated and still need a response. This catches cases where notifications aren't
generated (e.g. self-assignment, API-created issues).
The poller also runs a secondary **label scan** every 2 minutes, checking all
watched repos for open issues/PRs with the `bot` label that are unassigned. This
catches cases where the agent chain broke — an agent timed out or crashed
without spawning the next agent. It also picks up newly-labeled issues that
didn't trigger a notification.
Key design decisions:
- **The poller IS the dispatcher.** No flag files, no heartbeat dependency. The
poller triages notifications and spawns agents directly.
- **Marks notifications as read immediately.** Each notification is marked read
as it's processed, preventing re-dispatch on the next poll.
- **One agent per issue.** Each spawned agent gets a `SCOPE` instruction
limiting it to one specific issue/PR. Agents post results as Gitea comments,
not DMs.
- **Dedup tracking.** An in-memory `dispatched_issues` set prevents spawning
multiple agents for the same issue within one poller lifetime.
- **`--no-deliver` instead of `--announce`.** Agents report via Gitea API
directly. The `--announce` flag on isolated sessions had delivery failures.
- **Assignment scan filters by recency.** Only issues updated in the last 5
minutes are considered, preventing re-dispatch for stale assigned issues.
- **Zero dependencies.** Just Python stdlib. Runs anywhere.
- **Marks notifications as read immediately.** Prevents re-dispatch on the next
poll cycle.
- **Assigns the bot user at dispatch time.** Before spawning the agent, the
poller assigns the bot account to the issue via API. This prevents race
conditions — subsequent scans skip assigned issues. The spawned agent doesn't
need to claim ownership; it's already claimed.
- **Persistent dispatch tracking.** Dispatched issues are tracked in a JSON
file on disk (not just in memory), surviving poller restarts. Entries
auto-prune after 1 hour.
- **30-minute re-dispatch cooldown.** Safety net for broken agent chains. Normal
operation uses agent-to-agent chaining (each agent spawns the next), so the
poller only re-dispatches if the chain breaks.
- **Concurrency cap.** The poller checks how many agents are currently running
(`openclaw cron list`) and defers dispatch if the cap is reached.
- **Stale agent reaper.** Each scan cycle, kills agent sessions running longer
than 10 minutes. The `--timeout-seconds` flag isn't always enforced by
OpenClaw, so the poller handles cleanup itself.
- **`merge-ready` skip.** The label scan skips issues already labeled
`merge-ready` — those are in the human's court.
- **Template-based prompts.** The poller reads two workspace files (a dispatch
header with `{{variable}}` placeholders, and a workflow rules document),
concatenates them, substitutes variables, and passes the result as the
agent's `--message`. This keeps all instructions in version-controlled
workspace files with a single source of truth.
- **Zero dependencies.** Python stdlib only. Runs anywhere.
Response time: ~15–60s from notification to agent comment (vs ~30 min with the
old heartbeat approach).
Response time: ~15–30s from notification to agent starting work.
```python
#!/usr/bin/env python3
@ -231,20 +244,25 @@ old heartbeat approach).
Gitea notification poller + dispatcher.
Two polling loops:
1. Notification-based: detects new notifications (mentions, assignments by
other users) and dispatches agents for actionable ones.
2. Assignment-based: periodically checks for open issues/PRs assigned to
the bot that have no recent bot comment. Catches cases where
notifications aren't generated (e.g. self-assignment, API-created issues).
1. Notification-based: detects new @-mentions and assignments, dispatches
agents for actionable notifications.
2. Label-based: periodically scans for issues/PRs with the 'bot' label
that are unassigned (available for work). Catches broken agent chains
and newly-labeled issues.
The poller assigns the bot user to the issue BEFORE spawning the agent,
preventing race conditions where multiple scans dispatch for the same issue.
Required env vars:
GITEA_URL - Gitea instance URL
GITEA_TOKEN - Gitea API token
Optional env vars:
POLL_DELAY - Delay between polls in seconds (default: 15)
COOLDOWN - Minimum seconds between dispatches (default: 30)
ASSIGNMENT_INTERVAL - Seconds between assignment scans (default: 120)
POLL_DELAY - Seconds between notification polls (default: 15)
COOLDOWN - Seconds between dispatch batches (default: 30)
BOT_SCAN_INTERVAL - Seconds between label scans (default: 120)
MAX_CONCURRENT_AGENTS - Max simultaneous agents (default: 10)
REAP_AGE_SECONDS - Kill agents older than this (default: 600)
OPENCLAW_BIN - Path to openclaw binary
"""
@ -260,18 +278,50 @@ GITEA_URL = os.environ.get("GITEA_URL", "").rstrip("/")
GITEA_TOKEN = os.environ.get("GITEA_TOKEN", "")
POLL_DELAY = int(os.environ.get("POLL_DELAY", "15"))
COOLDOWN = int(os.environ.get("COOLDOWN", "30"))
ASSIGNMENT_INTERVAL = int(os.environ.get("ASSIGNMENT_INTERVAL", "120"))
OPENCLAW_BIN = os.environ.get("OPENCLAW_BIN", "/opt/homebrew/bin/openclaw")
BOT_USER = "clawbot" # Change to your bot's Gitea username
BOT_SCAN_INTERVAL = int(os.environ.get("BOT_SCAN_INTERVAL", "120"))
MAX_CONCURRENT_AGENTS = int(os.environ.get("MAX_CONCURRENT_AGENTS", "10"))
REAP_AGE_SECONDS = int(os.environ.get("REAP_AGE_SECONDS", "600"))
REDISPATCH_COOLDOWN = 1800 # 30 min safety net for broken agent chains
OPENCLAW_BIN = os.environ.get("OPENCLAW_BIN", "openclaw")
BOT_USER = os.environ.get("BOT_USER", "clawbot")
# Repos to scan for assigned issues
WORKSPACE = os.path.expanduser("~/.openclaw/workspace")
DISPATCH_HEADER = os.path.join(
WORKSPACE, "taskprompts", "how-to-handle-gitea-notifications.md"
)
WORKFLOW_DOC = os.path.join(
WORKSPACE, "taskprompts", "how-to-work-on-a-gitea-issue-or-pr.md"
)
DISPATCH_STATE_PATH = os.path.join(
os.path.dirname(os.path.abspath(__file__)), ".dispatch-state.json"
)
# Repos to watch for bot-labeled issues
WATCHED_REPOS = [
# "org/repo1",
# "org/repo2",
]
# Track dispatched issues to prevent duplicates
dispatched_issues = set()
# Dispatch tracking (persisted to disk)
dispatched_issues: dict[str, float] = {}
def _load_dispatch_state() -> dict[str, float]:
try:
with open(DISPATCH_STATE_PATH) as f:
state = json.load(f)
now = time.time()
return {k: v for k, v in state.items() if now - v < 3600}
except (FileNotFoundError, json.JSONDecodeError):
return {}
def _save_dispatch_state():
try:
with open(DISPATCH_STATE_PATH, "w") as f:
json.dump(dispatched_issues, f)
except OSError as e:
print(f"WARN: Could not save dispatch state: {e}", file=sys.stderr)
def gitea_api(method, path, data=None):
@ -290,17 +340,91 @@ def gitea_api(method, path, data=None):
return None
def needs_bot_response(repo_full, issue_number):
"""True if the bot is NOT the author of the most recent comment."""
comments = gitea_api("GET", f"/repos/{repo_full}/issues/{issue_number}/comments")
if comments and len(comments) > 0:
if comments[-1].get("user", {}).get("login") == BOT_USER:
return False
return True
def load_template() -> str:
"""Load dispatch header + workflow doc, concatenated."""
parts = []
for path in [DISPATCH_HEADER, WORKFLOW_DOC]:
try:
with open(path) as f:
parts.append(f.read())
except FileNotFoundError:
print(f"ERROR: File not found: {path}", file=sys.stderr)
sys.exit(1)
return "\n\n---\n\n".join(parts)
def render_template(template, repo_full, issue_number, title,
subject_type, reason):
return (
template
.replace("{{repo_full}}", repo_full)
.replace("{{issue_number}}", str(issue_number))
.replace("{{title}}", title)
.replace("{{subject_type}}", subject_type)
.replace("{{reason}}", reason)
.replace("{{gitea_url}}", GITEA_URL)
.replace("{{gitea_token}}", GITEA_TOKEN)
.replace("{{openclaw_bin}}", OPENCLAW_BIN)
.replace("{{bot_user}}", BOT_USER)
# Add your own variables here (e.g. git_channel)
)
def count_running_agents() -> int:
try:
result = subprocess.run(
[OPENCLAW_BIN, "cron", "list"],
capture_output=True, text=True, timeout=10,
)
return sum(1 for line in result.stdout.splitlines()
if "running" in line or "idle" in line)
except Exception:
return 0
def spawn_agent(template, repo_full, issue_number, title,
subject_type, reason):
dispatch_key = f"{repo_full}#{issue_number}"
last = dispatched_issues.get(dispatch_key)
if last and (time.time() - last) < REDISPATCH_COOLDOWN:
return
if count_running_agents() >= MAX_CONCURRENT_AGENTS:
print(f" → Concurrency limit reached, deferring {dispatch_key}",
flush=True)
return
dispatched_issues[dispatch_key] = time.time()
# Assign bot user immediately to prevent races
gitea_api("PATCH", f"/repos/{repo_full}/issues/{issue_number}",
{"assignees": [BOT_USER]})
repo_short = repo_full.split("/")[-1]
job_name = f"gitea-{repo_short}-{issue_number}-{int(time.time())}"
msg = render_template(template, repo_full, issue_number, title,
subject_type, reason)
try:
result = subprocess.run(
[OPENCLAW_BIN, "cron", "add",
"--name", job_name, "--at", "1s",
"--message", msg, "--delete-after-run",
"--session", "isolated", "--no-deliver",
"--thinking", "low", "--timeout-seconds", "300"],
capture_output=True, text=True, timeout=15,
)
if result.returncode == 0:
_save_dispatch_state()
else:
dispatched_issues.pop(dispatch_key, None)
except Exception as e:
print(f"Spawn error: {e}", file=sys.stderr, flush=True)
dispatched_issues.pop(dispatch_key, None)
def is_actionable(notif):
"""Returns (actionable, reason, issue_number)."""
"""Check if a notification warrants spawning an agent."""
subject = notif.get("subject", {})
repo = notif.get("repository", {})
repo_full = repo.get("full_name", "")
@ -313,68 +437,88 @@ def is_actionable(notif):
if not issue:
return False, "couldn't fetch issue", number
assignees = [a.get("login") for a in (issue.get("assignees") or [])]
if BOT_USER in assignees:
if needs_bot_response(repo_full, number):
return True, f"assigned to {BOT_USER}", number
return False, "assigned but already responded", number
issue_body = issue.get("body", "") or ""
if f"@{BOT_USER}" in issue_body and issue.get("user", {}).get("login") != BOT_USER:
if needs_bot_response(repo_full, number):
return True, f"@-mentioned in body", number
comments = gitea_api("GET", f"/repos/{repo_full}/issues/{number}/comments")
# Check for @-mentions in the latest comment
comments = gitea_api(
"GET", f"/repos/{repo_full}/issues/{number}/comments"
)
if comments:
last = comments[-1]
if last.get("user", {}).get("login") == BOT_USER:
return False, "own comment is latest", number
if f"@{BOT_USER}" in (last.get("body") or ""):
return True, f"@-mentioned in comment", number
return True, "@-mentioned in comment", number
return False, "not mentioned or assigned", number
# Check for @-mention in issue body
body = issue.get("body", "") or ""
if f"@{BOT_USER}" in body:
return True, "@-mentioned in body", number
return False, "not mentioned", number
def spawn_agent(repo_full, issue_number, title, subject_type, reason):
dispatch_key = f"{repo_full}#{issue_number}"
if dispatch_key in dispatched_issues:
return
dispatched_issues.add(dispatch_key)
def scan_bot_labeled(template):
"""Scan for issues/PRs with 'bot' label that are unassigned."""
for repo_full in WATCHED_REPOS:
for issue_type in ["issues", "pulls"]:
items = gitea_api(
"GET",
f"/repos/{repo_full}/issues?state=open&type={issue_type}"
f"&labels=bot&sort=updated&limit=10",
) or []
for item in items:
number = str(item["number"])
dispatch_key = f"{repo_full}#{number}"
repo_short = repo_full.split("/")[-1]
job_name = f"gitea-{repo_short}-{issue_number}-{int(time.time())}"
msg = (
f"Gitea: {reason} on {subject_type} #{issue_number} "
f"'{title}' in {repo_full}.\n"
f"API: {GITEA_URL}/api/v1 | Token: {GITEA_TOKEN}\n"
f"SCOPE: Only {subject_type} #{issue_number} in {repo_full}.\n"
f"Read all comments, do the work, post results as Gitea comments."
)
try:
subprocess.run(
[OPENCLAW_BIN, "cron", "add",
"--name", job_name, "--at", "1s",
"--message", msg, "--delete-after-run",
"--session", "isolated", "--no-deliver",
"--thinking", "low", "--timeout-seconds", "300"],
capture_output=True, text=True, timeout=15,
)
except Exception as e:
print(f"Spawn error: {e}", file=sys.stderr, flush=True)
dispatched_issues.discard(dispatch_key)
last = dispatched_issues.get(dispatch_key)
if last and (time.time() - last) < REDISPATCH_COOLDOWN:
continue
assignees = [
a.get("login", "") for a in item.get("assignees") or []
]
if BOT_USER in assignees:
continue
labels = [
l.get("name", "") for l in item.get("labels") or []
]
if "merge-ready" in labels:
continue
kind = "PR" if issue_type == "pulls" else "issue"
spawn_agent(
template, repo_full, number,
item.get("title", "")[:60],
"pull" if issue_type == "pulls" else "issue",
"bot label, unassigned",
)
def main():
print(f"Poller started (poll={POLL_DELAY}s, cooldown={COOLDOWN}s)", flush=True)
seen_ids = set(n["id"] for n in (gitea_api("GET", "/notifications?status-types=unread") or []))
global dispatched_issues
dispatched_issues = _load_dispatch_state()
if not GITEA_URL or not GITEA_TOKEN:
print("ERROR: GITEA_URL and GITEA_TOKEN required", file=sys.stderr)
sys.exit(1)
template = load_template()
print(f"Poller started (poll={POLL_DELAY}s, cooldown={COOLDOWN}s, "
f"bot_scan={BOT_SCAN_INTERVAL}s, repos={len(WATCHED_REPOS)})",
flush=True)
seen_ids = set(
n["id"] for n in
(gitea_api("GET", "/notifications?status-types=unread") or [])
)
last_dispatch = 0
last_assign_scan = 0
last_bot_scan = 0
while True:
time.sleep(POLL_DELAY)
now = time.time()
# Notification polling
# --- Notification polling ---
notifs = gitea_api("GET", "/notifications?status-types=unread") or []
current_ids = {n["id"] for n in notifs}
new_ids = current_ids - seen_ids
@ -388,28 +532,14 @@ def main():
repo = n["repository"]["full_name"]
title = n["subject"]["title"][:60]
stype = n["subject"].get("type", "").lower()
spawn_agent(repo, num, title, stype, reason)
spawn_agent(template, repo, num, title, stype, reason)
last_dispatch = now
seen_ids = current_ids
# Assignment scan (less frequent)
if now - last_assign_scan >= ASSIGNMENT_INTERVAL:
for repo in WATCHED_REPOS:
for itype in ["issues", "pulls"]:
items = gitea_api("GET",
f"/repos/{repo}/issues?state=open&type={itype}"
f"&assignee={BOT_USER}&sort=updated&limit=10") or []
for item in items:
num = str(item["number"])
if f"{repo}#{num}" in dispatched_issues:
continue
# Only recently updated items (5 min)
# ... add is_recently_updated() check here
if needs_bot_response(repo, num):
spawn_agent(repo, num, item["title"][:60],
"pull" if itype == "pulls" else "issue",
f"assigned to {BOT_USER}")
last_assign_scan = now
# --- Bot label scan (less frequent) ---
if now - last_bot_scan >= BOT_SCAN_INTERVAL:
scan_bot_labeled(template)
last_bot_scan = now
if __name__ == "__main__":
@ -754,25 +884,27 @@ From REPO_POLICIES.md and our operational experience:
#### The PR Pipeline
Our agent follows a strict PR lifecycle:
Our agent follows a strict PR lifecycle using agent-to-agent chaining. Each step
is handled by a separate, isolated agent session — the agent that writes code
never reviews it:
```markdown
## PR pipeline (every PR, no exceptions)
1. **Review/rework loop**: code review → rework → re-review → repeat until clean
2. **Check/rework loop**: `make check` + `docker build .` → rework → re-check →
repeat until clean
3. Only after BOTH loops pass with zero issues: assign to human
Worker agent → docker build . → push → label needs-review → spawn reviewer
Reviewer agent → review diff → PASS: docker build . → label merge-ready
→ FAIL: label needs-rework → spawn worker
Repeat until reviewer approves.
- "Passes checks" ≠ "ready for human"
- docker build . is the ONLY authoritative check (runs make check inside)
- Never weaken tests/linters. Fix the code.
- Pre-existing failures are YOUR problem. Fix them as part of your PR.
```
The agent doesn't just create a PR and hand it off — it drives the PR through
review, rework, and verification until it's genuinely ready. A PR assigned to
the human means: all checks pass, code reviewed, review feedback addressed,
rebased against main, no conflicts. Anything less is the agent's open task.
The agent chain doesn't just create a PR and hand it off — it drives the PR
through review, rework, and verification until it's genuinely ready. A PR
assigned to the human means: build passes, code reviewed by a separate agent,
review feedback addressed, rebased. Anything less is still in the agent chain.
#### New Repo Bootstrap
@ -1624,12 +1756,12 @@ For complex coding tasks, spawn isolated sub-agents.
### Sub-Agent PR Quality Gate (MANDATORY)
- `make check` must pass with ZERO failures. No exceptions.
- `docker build .` must pass. This is identical to CI and the only
authoritative check. No exceptions.
- Pre-existing failures are YOUR problem. Fix them as part of your PR.
- NEVER modify linter config to make checks pass. Fix the code.
- Every PR must include full `make check` output
- Rebase before and after committing
- Never self-review
- Never self-review — each agent spawns a separate agent for review
```
---