debrief

REVIEW · 68
Registry indexed

Post-interview review — reconstructs the Q&A from transcript or memory, captures interviewer intel and next-round forecasts, and turns the round into a revision list for the script. Use when the user says they just finished an interview, 刚面完 / 复盘一下 / 面试录音转文字给你 / 这轮被问了什么, or paste

Verified installs0
Stars11
Version1.0.0
Quality58/100 · Promising
Trust68/100 · Sandbox only
Audit78/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

Scenario

Research agents

I need my agent to research a topic, compare sources, and produce a concise report.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add YunyueLi/greenroom --skill debrief

Maintenance

fresh

Pushed today

Risk

Needs review

Low GitHub adoption signal

GitHub quality

11

58/100 Quality · 76/100 Trust

Coverage tags

ResearchResearch agentsagent-skill

Review notes

Low GitHub adoption signal · Quality score needs review

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
58

Useful candidate, but compare it with alternatives before adopting.

Trust

Sandbox only
68

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
78

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

11 GitHub stars

Repo activity

11 stars, 1 forks

Maintenance

Pushed today

License

AGPL-3.0

Install

npx skills add YunyueLi/greenroom --skill debrief

Install safety

standard package or runtime install path

Permission surface

no high-risk permission surface in public metadata

Agent outcomes

No agent outcome data yet

Docs

Usable metadata, review docs

Risk summary

Review before production

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 11 GitHub stars
  • Stars/forks activity: 11 stars, 1 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Search sources

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add YunyueLi/greenroom --skill debrief
Policy
review
Human review
yes

Trust and risk

Trust
68/100
Audit
78/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add YunyueLi/greenroom --skill debrief

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • No OpenAgentSkill engagement data yet
  • Quality score needs review

Agent safety v2

66/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

  • Low GitHub adoption signal

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install yunyueli-debrief

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use debrief in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20debrief%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yunyueli-debrief/install
Install command: npx skills add YunyueLi/greenroom --skill debrief
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use debrief for this task. Review https://www.openagentskill.com/api/skills/yunyueli-debrief/install, then install with: npx skills add YunyueLi/greenroom --skill debrief

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

57/100

Research agents

Platforms

Claude Code

Audit report

Needs review · 78/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Needs validation for Research agents

Do a manual repository review before adding this to an agent workflow.

57
Readiness
Review
Stage

Role in stack

Needs validation

Primary fit

Research agents

Trust label

Needs manual review

Install path

Command ready

Use when

  • Research agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 58/100 quality profile

review first

  • Low GitHub adoption signal
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Research agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

68
OpenAgentSkill Trust Score

GitHub adoption

FIX

11 GitHub stars

Stars/forks activity

FIX

11 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

AGPL-3.0

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 11 GitHub stars
  • Stars/forks activity: 11 stars, 1 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

58
GitHub stars
11
Freshness
Today
Install ready
Yes
License
AGPL-3.0
Review before install: Low GitHub adoption signal

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: debrief description: Post-interview review — reconstructs the Q&A from transcript or memory, captures interviewer intel and next-round forecasts, and turns the round into a revision list for the script. Use when the user says they just finished an interview, 刚面完 / 复盘一下 / 面试录音转文字给你 / 这轮被问了什么, or pastes an interview transcript or recollection. Do NOT use for practice sessions (mock-interview) or pre-interview research (job-intel). license: AGPL-3.0 metadata: author: Yunyue Li version: "0.1.0" ---

# debrief · 面后复盘

每轮真实面试后 24 小时内做一次(记忆衰减很快)。产出 `jobs/<slug>/rounds/rN-debrief.md`:把这一轮固化成下一轮能用的东西——问答复原、面试官情报、下轮预测、逐字稿修订清单。

## 输入采集

最好的输入是录音转写。没有就引导回忆倾倒,按这个顺序问(一次 2-3 个问题,别审讯):

1. 从进场开始按时间顺序过:第一个问题是什么?你怎么答的? 2. 每个问题:面试官当时的反应(追问了?点头?记笔记?换话题?) 3. 哪几题答得不顺、答完自己不满意,或被追问到答不上来? 4. 面试官透露了什么:团队情况、岗位实情、下轮安排、他自己的背景 5. 反问环节你问了什么、对方答了什么

明确告诉用户:记不清的就说记不清,复原里会标「不确定」,比硬凑可靠。

## 产出 rN-debrief.md

frontmatter:`type: debrief / job: <slug> / round: N / updated: <date>`。四个部分:

### 1. 问答复原

按时间顺序,`**Q:**` / `**A:**`(A 记要点和关键原话)。不确定处标 `(不确定)`。面试官的反应用括号注在对应位置。

### 2. 面试官情报更新

观察到的风格(追问型?要数字型?)、在意什么(哪个话题追了三层)、他主动透露的信息(团队/方向/他的背景)。回写进 `intel.md` 的面试官档案。

### 3. 下轮预测与建议

- 本轮剧透的下轮信息:谁面、考什么(面试官经常顺嘴说"下一轮会让你聊聊 X"——这是最高价值情报) - 本轮暴露的弱点 → 下轮大概率重点核查的点 - 给 interview-script 的修订清单:哪些题答得不顺要重写、下轮要新增什么题

### 4. 待办

按优先级列 3-5 条(核实什么、补什么材料、改什么稿、跟猎头确认什么)。

## 收尾

汇报:复原了几题、面试官情报更新了什么、下轮预测、建议的下一步(通常是按修订清单回 interview-script 改稿)。

Technical details

Version
1.0.0
License
AGPL-3.0
Last updated
Aug 23, 2026
Published
Aug 23, 2026

Decision snapshot

Needs validation

57
Ready
Review
Stage

recent repository activity

Audit

Install review

Install and adoption review

78
Needs review
Security
87/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for debrief, ready for a manual X post.

Curator note
debrief: Post-interview review — reconstructs the Q&A from transcript or memory, captures interviewer...

11 stars

https://www.openagentskill.com/skills/yunyueli-debrief?ref=x
Open X draft
Optional reply with install command
Listing + install path for debrief:
https://www.openagentskill.com/skills/yunyueli-debrief?ref=x

Install: npx skills add YunyueLi/greenroom --skill debrief

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
YunyueLi
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Registry indexed listing is attributed to YunyueLi but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/yunyueli-debrief?metric=listed&label=Listed)](https://www.openagentskill.com/skills/yunyueli-debrief)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/yunyueli-debrief?metric=trust&label=Trust)](https://www.openagentskill.com/skills/yunyueli-debrief)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/yunyueli-debrief?metric=audit&label=Audit)](https://www.openagentskill.com/skills/yunyueli-debrief/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/yunyueli-debrief?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/yunyueli-debrief)

Author

Y

YunyueLi

@yunyueli

Platform fit

Health signals

GitHub stars
11
Quality score
31/100
Last GitHub push
Aug 23, 2026
Framework hints
Unknown
OpenAgentSkill views
0
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Sandbox only

68
  • GitHub adoption11 GitHub starsFIX
  • Stars/forks activity11 stars, 1 forks; issue activity unavailable in current metadataFIX
  • Recent maintenancePushed todayPASS
  • License clarityAGPL-3.0PASS
  • README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
  • Dependency/runtime riskno major dependency risk hints in public metadataPASS