Marcos
6e3a9eb5b0
Replace the single Python model-call reviewer with an opencode agent
factory. A primary 'pragent' agent reads a brief (title/body/diff/config/
prior reviews), inspects the checked-out repo, runs the repo's own linters
via bash, loads review-methodology + findings-schema skills, and emits a
{summary, findings} JSON with per-finding severity/path/line/problem/fix/
suggestion/reference. Dormant security/tests/perf subagent lenses fan out
only on large/risky diffs (lean by default).
pilot/opencode_review.py: fetches the repo archive at the head sha into a
temp workdir, writes .pragent/brief.md, drops the factory, runs
'opencode run --pure --agent pragent --dir <workdir>' headlessly. Isolates
HOME (shared, warmed), strips ANTHROPIC_* env (leaked host vars caused
ProviderModelNotFoundError), stdin=DEVNULL (opencode blocks on stdin),
maps the bare OLLAMA_MODEL to the provider-prefixed ref. No Gitea I/O —
ai_review.review_pr parses + anchors + posts (reuses all v2 logic/tests).
PRAGENT_ENGINE=opencode (default) selects it; =ollama keeps the legacy
direct-call path. Verified end-to-end: posts a real review with a summary
section, inline [CRITICAL]/[HIGH] comments + apply-able suggestions +
reference links, and the sha dedupe marker. 49 tests pass.
Co-Authored-By: Claude <noreply@anthropic.com>
1.9 KiB
1.9 KiB
description, mode, hidden, model, temperature, permission
| description | mode | hidden | model | temperature | permission | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Security lens subagent. Scans a PR diff for injection, auth, secret, and supply-chain risks and returns findings JSON. Invoked by the pragent primary on large or security-sensitive diffs. | subagent | true | headroom/glm-5.2:cloud | 0.1 |
|
You are a security reviewer subagent. The pragent primary hands you a PR's diff (and the checked-out repo). Hunt ONLY for security issues:
- Injection: SQL/NoSQL/LDAP/command/template injection, unsanitized input flowing into interpreters. SQL must use parameterized queries / prepared statements — flag string-built queries.
- Auth & access control: broken auth checks, missing authorization, insecure
token/session handling, password compared with
==(use constant-time compare). - Secrets: hardcoded credentials, API keys, private keys committed, secrets in logs/URLs/error messages.
- Supply chain: suspicious new dependencies, typosquats,
eval/exec/new Functionon user input, unsafe deserialization, SSRF, path traversal. - Crypto: weak algorithms (MD5/SHA1 for security), homemade crypto, bad random
(
Math.random/randomfor tokens).
Use webfetch to confirm a CVE or library footgun and cite it in reference.
Read surrounding code from the checked-out repo when a sink's data flow isn't
clear from the diff alone.
Return STRICT JSON only — same shape as the pragent primary's findings, but security findings only:
{"findings":[{"severity":"critical|high|medium|low","path":"...","line":0,"problem":"...","fix":"...","suggestion":"...","reference":"https://..."}]}
line must be a post-change (context or +) line. Empty suggestion when no
safe replacement. No prose outside the JSON block.