From legal-clinic
Manages a formal review queue for legal clinic supervisors: view pending items by urgency or student, approve, edit-then-approve, or return with notes. Only active when 'formal review queue' supervision style is configured.
How this skill is triggered — by the user, by Claude, or both
Slash command
/legal-clinic:supervisor-review-queue [--approve ID | --return ID 'note' | --edit ID][--approve ID | --return ID 'note' | --edit ID]The summary Claude sees in its skill listing — used to decide when to auto-load this skill
1. Check `~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md` → supervision style. If NOT "formal review queue": explain the clinic is set up for [flags/lighter-touch], no formal queue exists, and how to switch.
~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md → supervision style. If NOT "formal review queue": explain the clinic is set up for [flags/lighter-touch], no formal queue exists, and how to switch./legal-clinic:supervisor-review-queue
/legal-clinic:supervisor-review-queue --approve Q-003
/legal-clinic:supervisor-review-queue --return Q-004 "Check the service requirement — local rules changed"
Some clinics want a formal gate: student drafts, professor reviews, output releases. Others find that too prescriptive — they supervise through case rounds and one-on-ones, not through a queue.
This skill is only active if ~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md → Supervision style is "formal review queue." Otherwise it's dormant — the cold-start interview asks the professor which model they want, and this is one of three options.
Whether to use a formal review workflow is genuinely an open question for clinic adoption. It depends on student experience level, caseload, and how the professor already runs supervision. The professor decides at setup and can change it later.
~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md → supervision style. If NOT "formal review queue": respond with "The clinic is set up for [flags/lighter-touch] supervision — there's no formal queue. [Professor] reviews through [the clinic's existing structure]. To switch to a formal queue, edit CLAUDE.md → Supervision style."
If formal queue IS enabled → read flag triggers and proceed.
Lives at references/review-queue.yaml. Each entry:
- id: Q-001
type: "draft" # intake | draft | memo | status | client-letter
client: "[name or ID]"
student: "[name]"
submitted: [timestamp]
flags:
- rule: "Court filing"
detail: "Eviction answer — always queued"
content_path: "[path to the document]"
status: "pending" # pending | approved | edited-approved | returned
## Review Queue — [date]
**Pending:** [N] | **Oldest:** [N] hours
### 🔴 Deadline-sensitive
| ID | Type | Client | Student | Why flagged | Waiting |
|---|---|---|---|---|---|
### Standard
[same table]
### By student
[Breakdown — spot patterns: who's queueing a lot, who might need a check-in]
Show full content + why it was flagged + student notes.
Every action logged. Approval logs are clinic records — they document that a licensed attorney, solicitor, barrister, or other authorised legal professional in the clinic's jurisdiction reviewed student work before it went to a client or court. That matters for the clinic's own compliance and for student evaluation.
The queue is also data. Pattern in returns ("Student X keeps missing the service requirement") is a coaching conversation. Pattern in edits ("Everyone's demand letters are too long") is a /ramp update for next semester.
npx claudepluginhub zekaisuni/claude-for-legal-turkish --plugin legal-clinicManages a formal review queue for legal clinic supervisors: view pending items by urgency or student, approve, edit-then-approve, or return with notes. Only active when 'formal review queue' supervision style is configured.
Manages a formal review queue where staff output awaits attorney approval before release, with support for approve, edit-approve, return, and emergency prioritization.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.