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Survey a corpus, classify, and dispatch outputs. Three modes: retro (transcript review → issues), trend (longitudinal performance analysis), sweep (GitHub issue triage → fix-epics). Delegates execution to pauli (retro/trend) or jr (sweep) to keep main context clean.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/nicsuzor/aops --skill survey명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
Core academicOps skill — institutional memory, strategic coordination, workflow routing, and framework governance. Merges butler (chief-of-staff) with framework development conventions.
Daily note lifecycle — compose and maintain a factual daily note. Reports the state of the day; does not prioritise or recommend. SSoT for daily note structure.
Emergency session bail — fast resume task + short handover, no commit/PR/reflection. For when you (or the user) need a clean context now. Use /end-session for canonical close.
SKILL.md 표시 중
| name | survey |
| type | skill |
| category | instruction |
| description | Survey a corpus, classify, and dispatch outputs. Three modes: retro (transcript review → issues), trend (longitudinal performance analysis), sweep (GitHub issue triage → fix-epics). Delegates execution to pauli (retro/trend) or jr (sweep) to keep main context clean. |
| triggers | ["survey","retro","transcript review","session review","trend review","performance trends","issue sweep","triage issues"] |
| modifies_files | true |
| needs_task | false |
| mode | orchestration |
| domain | ["framework","quality-assurance","operations"] |
| allowed-tools | Agent, Bash, Read, Grep, Glob, Edit, Write, Skill, AskUserQuestion, mcp__pkb__list_tasks, mcp__pkb__get_task, mcp__pkb__create_task, mcp__pkb__update_task, mcp__pkb__append, mcp__pkb__task_search |
| owner | junior |
| version | 1.0.0 |
| tags | ["retro","trend","sweep","quality","consolidation"] |
Survey a corpus, classify findings, and dispatch outputs according to the selected mode.
| Mode | Corpus | Primary output |
|---|---|---|
retro | Session transcripts (one at a time) | GitHub issues filed via gh |
trend | Many sessions / audit files | Trend report + recommendations |
sweep | Open GitHub issues | PKB tasks, fix-epics, closures |
Privacy Rule: Anonymize all findings. Do not expose real names, emails, student details, or raw session dumps.
This skill delegates execution to keep the main context clean:
retro / trend mode: Dispatch pauli with access to PKB and system tools.sweep mode: Dispatch jr to handle interactive triage and confirmation gates.Perform a critical, forensic review of a single session transcript, apply immediate fixes where appropriate, and file the tracking GitHub issues.
pauli dispatched within the session) is explicitly allowed and structurally sound because the subagent executes in a clean, detached context.$AOPS_SESSIONS is set and $AOPS_SESSIONS/transcripts exists. If not, stop and ask the user.$AOPS_SESSIONS/transcripts/YYYY-MM/*-${SID}-*-claude-full.md. Use -abridged.md only as a fallback.$AOPS_SESSIONS/transcripts/YYYY-MM/-full.md file..jsonl — a forensic review on a degraded transcript yields false findings; proceed on raw JSONL only with explicit user confirmation./craft defects: compliance framing, missing artifact chain, etc.)./learn that last task should have been xyz: When Nic invokes this style with a description of what should have happened, treat it as a directive to perform a dual action:
When the transcript shows an artifact whose premise a sharp principal would have bounced — "was this a good idea?" answered no; good, working, well-tested work done for a bad idea (canonical instance: a deterministic rig — regex/threshold/NLP/checklist — built for a call a smart agent should just make, judgment-non-delegable) — that nonetheless passed review, classify it as a bad-premise approval and score the miss against the reviewer who approved it, not only the author:
/verify / rbg / pauli). Each of those carries a forced step-0 Premise Test (canonical definition: [[premise-test.md]]); an approval means that forcing function was skipped or rationalised past — a reviewer failure, with test-passing as its expected surface, never an excuse.This makes the reviewer's miss visible and attributed — the compounding fix for floor-optimisation (#1585): a slipped-through bad premise becomes a logged, attributed miss instead of an invisible one, so the cost lands on the surface that should have caught it.
Produce a review in this exact format. Keep text concise:
## Transcript Review: <filename>
**Session**: <session_id> **Date**: <date> **Project**: <project>
**Verdict**: [EXCELLENT | GOOD | ADEQUATE | POOR | FAILING]
### Findings
[Concise description of failures/successes, grouped by structural cause.]
### Patterns (Optional)
[Upstream/structural root cause spanning multiple findings.]
gh issue list and gh pr list to avoid duplication.gh issue edit.Bug: <brief-slug>.reviewed_by block.uv run pytest) to verify no regressions were introduced.| Anti-pattern | What to do instead |
|---|---|
| Same-context self-grading (the same agent reviewing their own work within the same conversation/turn context without a fresh reviewer boundary) | Review by a fresh subagent (like pauli dispatched within the same session) or a separate reviewer, ensuring a detached/clean review context. Same-session review by a fresh subagent is structurally sound and explicitly allowed. |
Including remediation proposals in the report (recusal) | Stop at facts, structural context, and impact. Propose fixes directly in the codebase (if permitted) but keep the filed issue strictly forensic. |
| Citing a single session as justification for a new mechanism | Recurrence is the evidence base for framework change, not the salience of a single transcript. |
Review multiple sessions to identify systemic effectiveness and trends.
Analyze aggregate true/false rates, temporal trends, coverage, and cost-benefit. Produce a report in this format:
# Trend Review: <Component Name>
**Question**: <review question> **Date**: <today>
**Corpus**: <N> files, <date range> **Sample**: <N> files (criteria: ...)
## Executive Summary
[3-5 sentences summarizing if the system is working and the main trend/issues.]
## Objectives Verdict
| Objective | Verdict | Evidence |
| --------- | -------------------------------------------- | -------- |
| [obj 1] | ANSWERED / PARTIALLY ANSWERED / UNANSWERABLE | [why] |
## Individual Assessments
### <filename> (<date>)
- **Context**: ... **Component behavior**: ... **Accuracy**: [TP/FP/FN] **Impact**: ...
## Aggregate Analysis
[Signal Quality / Temporal Trends / Coverage Map / Cost-Benefit]
## Recommendations
[Actionable, prioritized recommendations with evidence citations.]
## Confidence and Limitations
Save the report to ~/.aops/sessions/reviews/<component>-trend-<date>.md.
Triage and process open issues on nicsuzor/academicOps (batch limit: ≤20 issues).
Fetch open issues, focusing on the focal issue first if a directed focus is provided. Classify using this rubric:
| Disposition | Criterion | Action | Label |
|---|---|---|---|
close-as-stale | >90d old, no activity, or describes retired behavior. | Close issue with explanatory comment. | triaged-stale |
consolidate-duplicate | Describes the same underlying problem. | Merge details into canonical issue; close duplicate with cross-link comment (#N). | triaged-duplicate |
aggregate | Multiple issues sharing one root cause/fix surface. | Fold into one fix-epic task (leave queued); close source issues with pointer comments. | triaged-aggregate |
evidence-bump | Accumulates evidence for a related open issue/epic. | Leave open; add comment citing canonical issue (#N). | triaged-evidence-bump |
single-task | Atomic task (AC clear, ≤3 files, obvious fix). | File polecat task with Closes #N. | triaged-single |
fix-epic | Multi-step, multi-file, or design-required work. | Create epic task and decompose, leave queued. | triaged-epic |
defer | Real but blocked or low-criticality. | Apply defer label and revisit-by date. | triaged-defer |
For proposals that add or escalate a rule, perform this review before assigning the disposition:
specs/ENFORCEMENT-MAP.md rows as a pipeline gap.Log results in the following format:
## Cycle <N> — applied (open before: <K>; batch: <M>)
### Applied autonomously (done)
- Consolidate-duplicate: #R → unique detail merged into #S, #R verified state:closed
- Aggregate: #A, #B, #C → folded into fix-epic <id> (queued)
- Evidence bump: #T → bumped #U
- Close (stale): #P
- Defer: #Q (revisit-by YYYY-MM-DD)
- Single-task: #X → "<title>"
- Fix-epic (queued): <title> ← #D, #E
### Needs human triage / decision (waiting)
- #Z (rubric ambiguous: <reason>)
- <add-or-escalate proposal>: cost-ladder reasoning + ≥3 recurrence links
severity (or set severity=0) on tasks created during the sweep. Assigning non-zero severity to ordinary tasks is prohibited; severity belongs exclusively on target milestones (see [[../remember/references/TAXONOMY.md#severity-target-boundary]]).priority=0 (P0) on swept tasks unless it is deliberately calibrated under canonical rules (see [[../remember/references/TAXONOMY.md#p0-calibration-bar]]) and explicitly requested/justified.state: closed.epic-a0523a25 and append the cycle log details.Skill(skill="verify", args="Verify cycle <N> of /issue-sweep on epic-a0523a25.")