Step 5: Publish (Phase 3)

Module: junior.publish.local.post_review() via junior.publish.core.formatter.format_summary()

Input

• ReviewResult from Step 4
• Settings (for footer metadata)

Output: Formatted Markdown (99 lines)

Written to /tmp/junior_review_output.md.

Every run also writes a secret-free JSON record to <project_dir>/.junior/output/{timestamp}.json (on by default for auditability; disable with --no-record).

Header

## Junior Code Review

The code quality is poor overall, with multiple critical security flaws
that must be addressed immediately: unsafe `eval`, command injection via
`shell=True`, SQL injection in several helpers, weak token handling,
hardcoded secrets, and MD5 password hashing...

Findings Table

| Severity | Count |
|----------|-------|
| 🔴 Critical | 5 |
| 🟠 High | 20 |
| 🟡 Medium | 13 |

Detailed Findings (grouped by severity)

#### Critical
- **[security]** `api.py:93` -- `process_webhook()` uses `eval(payload)`...
  - Suggestion: Parse the payload with `json.loads()`...

#### High
- **[security]** `auth.py:55` -- `check_permission()` returns `True`...
  - Suggestion: Fail closed: return `False` for unknown roles...
...

#### Medium
- **[security]** `hello.py:29` -- `load_contacts()` accepts arbitrary file_path...
  - Suggestion: Restrict reads to a fixed directory...

Footer

---
*Reviewed by [Junior AI](https://github.com/mishachepi/junior/) | pydantic | gpt-5.4-mini | 28,174 in / 7,224 out tokens*

Data Flow Summary

CollectedContext (Step 1)
    |
    v
build_user_message() (Step 2) ---> User Message (12KB markdown)
    |
    v
prompt_loader (Step 3) ----------> System Prompt (4KB, merged into one)
    |
    v
pydantic harness (Step 4) -------> ReviewResult (38 findings, 35K tokens)
    |
    v
format_summary() (Step 5) -------> Formatted Review (99 lines markdown)
    |
    v
local.post_review() -------------> /tmp/junior_review_output.md (or stdout)