Star0

Afterglow

REVIEW · 72
Community indexed

使用 QQ/微信 聊天记录结合向量数据库让AI更好的扮演对方的角色，在不微调模型的情况下可以达到可观的效果。把曾经的美好，续成往后的陪伴。 --续温

Downloads0
Stars104
Version1.0.0
Quality77/100 · Strong
Trust72/100 · Sandbox only
Audit85/100 · Safe to try

Supply asset profile

Research and knowledge work

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

Browse track

Scenario

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Agent fit

Claude Code + CLI + Codex

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

Install

Ready

npx skills add kldhsh123/Afterglow

Maintenance

fresh

14d since push

Risk

Safe to try

Quality score needs review

GitHub quality

104

77/100 quality · 80/100 trust

Coverage tags

ResearchRAG and knowledgerag-knowledgeragretrieval

Review notes

Quality score needs review · Stars/forks activity: 104 stars, 15 forks; issue activity unavailable in current metadata

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

Strong
77

Solid option that is likely worth shortlisting for production workflows.

Trust

Sandbox only
72

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

Audit

Safe to try
85

Install readiness, security metadata, maintenance, and adoption risk.

Trust Score v5

Human review before install

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

PythonRAGCodexClaude CodeCursor

Stars

104 GitHub stars

Repo activity

104 stars, 15 forks

Maintenance

14d since push

License

AGPL-3.0

Install

npx skills add kldhsh123/Afterglow

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Usable metadata, review docs

Risk summary

Review before production

  • Quality score needs review
  • Stars/forks activity: 104 stars, 15 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

  • RAG and knowledge workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Chunk documents

Suited agents

PythonRAGCodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add kldhsh123/Afterglow
Policy
review
Human review
yes

Trust and risk

Trust
72/100
Audit
85/100
Risk level
Safe to try

Outcome loop

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

Install command

npx skills add kldhsh123/Afterglow
Public auditEval reportResolve APIInstall handoff

Do not use when

  • teams that need a vendor-supported SLA
  • high-compliance environments without internal security review
  • No OpenAgentSkill engagement data yet
  • Quality score needs review
  • Stars/forks activity: 104 stars, 15 forks; issue activity unavailable in current metadata

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Agent safety v2

69/100 · Review before install

Reviewedreview

Good audit and safety signals with no high-risk permission hints in public metadata.

Review the audit page, then allow agent install in a sandboxed workflow.

Resolve via API

medium

Network access

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

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • Quality score needs review

Install targets

Install this skill in your agent workflow

Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add kldhsh123/Afterglow

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

Resolve JSON

/api/agent/resolve?task=Use%20Afterglow%20for%20an%20agent%20workflow&agent=codex&max_risk=medium

Resolve text

/api/agent/resolve?task=Use%20Afterglow%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text

Install handoff

/api/skills/kldhsh123-afterglow/install

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 Afterglow in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Afterglow%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/kldhsh123-afterglow/install
Install command: npx skills add kldhsh123/Afterglow
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

Install handoff

/api/skills/kldhsh123-afterglow/install

LLM text format

/api/skills/kldhsh123-afterglow/install?format=text

Find alternatives

/api/skills/search?q=Afterglow&limit=3

Agent prompt

Use Afterglow for this task. Review https://www.openagentskill.com/api/skills/kldhsh123-afterglow/install, then install with: npx skills add kldhsh123/Afterglow

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

Manifest

/api/registry/manifest/kldhsh123-afterglow

LLM text

/api/registry/manifest/kldhsh123-afterglow?format=text

Install alias

/api/registry/install/kldhsh123-afterglow

Recommend

/api/registry/recommend?task=Use%20Afterglow%20in%20an%20agent%20workflow&limit=3

Agent fit

76/100

RAG and knowledge

Use-case tags

RAG and knowledgeCoding agentsWorkflow automation

Platforms

Python, RAG, Claude Code

Audit report

Safe to try · 85/100

Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.

View audit reportView eval report

Agent decision cockpit

Companion skill for RAG and knowledge

Shortlist this skill and compare it with close alternatives before production adoption.

76
Readiness
Shortlist
Stage

Role in stack

Companion skill

Primary fit

RAG and knowledge

Trust label

Strong shortlist

Install path

Command ready

Use when

  • RAG and knowledge workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 77/100 quality profile

Review first

  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one RAG and knowledge 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.

72
Trust score

GitHub adoption

INFO

104 GitHub stars

Stars/forks activity

CHECK

104 stars, 15 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

14d since push

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

  • Quality score needs review
  • Stars/forks activity: 104 stars, 15 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

Strong candidate for agent workflows

Solid option that is likely worth shortlisting for production workflows.

77
GitHub stars
104
Freshness
14d ago
Install ready
Yes
License
AGPL-3.0

Workflow fit

Use this skill in these scenarios

Search private knowledge

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Build and ship code

Coding agents

I need a coding agent that can understand a repository, edit code, and review pull requests.

Automate repeated work

Workflow automation

I need my agent to automate a repeated workflow across tools and files.

Stack fit

Add it to a complete workflow

Ingest, retrieve, and cite

RAG knowledge base

A stack for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.

Turn skills into distribution

Content growth agent

A stack for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.

Inspect, patch, and verify code

Coding review agent

A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.

Alternative shortlist

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Overview

使用 QQ/微信 聊天记录结合向量数据库让AI更好的扮演对方的角色，在不微调模型的情况下可以达到可观的效果。把曾经的美好，续成往后的陪伴。 --续温

Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.

Platform Compatibility

pythonFULL
ragFULL

Technical Details

Version
1.0.0
License
AGPL-3.0
Last Updated
6/21/2026
Published
6/21/2026

Frameworks & Tools

PythonRAG

Decision snapshot

Companion skill

76
Ready
Shortlist
Stage

recent repository activity

Audit snapshot

Install review

Install and adoption review

85
Safe to try
Security
87/100
Maintenance
100/100
Install
92/100
Open full auditOpen 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.

Agent-Proven rankingOutcome contract

Install

Add to agent workflow

Free and open source. Review the audit before production use.

Compare AlternativesAuto-resolve PlanView on GitHubDocumentation

Growth loop

Share kit

X

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

Curator note
The useful research skills are not search wrappers. They help agents keep sources attached.

Afterglow helps agents turn docs, data, or knowledge bases into grounded work.

104 stars

https://www.openagentskill.com/skills/kldhsh123-afterglow?ref=x
#AIAgents
Open X draft
Optional reply with install command
Listing + install path for Afterglow:
https://www.openagentskill.com/skills/kldhsh123-afterglow?ref=x

Install: npx skills add kldhsh123/Afterglow
Open reply draft

Listing source

Community indexed

Claimable

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

Creator
kldhsh123
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 community indexed listing is attributed to kldhsh123 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.

README badge

Add this badge to your GitHub README to show the listing, trust score, and install handoff.

[![OpenAgentSkill](https://www.openagentskill.com/api/badge/kldhsh123-afterglow)](https://www.openagentskill.com/skills/kldhsh123-afterglow)
Preview badgeAudit badge

Author

K

kldhsh123

@kldhsh123

Tags

ragretrievalknowledgeafterglowai-companiondigital-companionlancedbllmpythonqq-chat

Platform Fit

Claude Code

Health Signals

GitHub stars
104
Quality score
48/100
Last GitHub push
Jun 19, 2026
Framework hints
2
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

72
  • GitHub adoption104 GitHub starsINFO
  • Stars/forks activity104 stars, 15 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenance14d since pushPASS
  • 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

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