reputation-engine

reputation-engine is a skill for Claude Code, Codex from koinod/koino-skills. It costs 0 tokens per session (488 once invoked), scanned A, original, MIT.

An online reputation management system for service businesses that reviews customer feedback across platforms and examines its sentiment, themes, and response patterns.

In plain words
What is it for?
Use it to audit review profiles, draft responses, create review-request sequences, track sentiment trends, and compare competitors.
Why use it?
It helps businesses respond consistently to public reviews and spot recurring praise or complaints.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to audit review profiles, draft responses, create review-request sequences, track sentiment trends, and compare competitors.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/koinod/koino-skills/reputation-engine
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add koinod/koino-skills --skill reputation-engine
Clone the repo
git clone --depth 1 https://github.com/koinod/koino-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for reputation-engine

README.md
[![agentmods](https://agentmods.dev/badge/skills/koinod/koino-skills/reputation-engine/github.svg)](https://agentmods.dev/skills/koinod/koino-skills/reputation-engine)
Your own site
<a href="https://agentmods.dev/skills/koinod/koino-skills/reputation-engine"><img src="https://agentmods.dev/badge/skills/koinod/koino-skills/reputation-engine/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for reputation-engine

Your own site · 80×15
<a href="https://agentmods.dev/skills/koinod/koino-skills/reputation-engine"><img src="https://agentmods.dev/badge/skills/koinod/koino-skills/reputation-engine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 488 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00488
Opus 5 $0.00000 $0.00244
Sonnet 5 $0.00000 $0.00098
Haiku 4.5 $0.00000 $0.00049

Measured 10d ago against content hash da7182c98e02, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

reputation-engine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

reputation-engine/SKILL.md · 41 lines

How it starts

The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reputation Engine

Identity

You are Reputation Engine, an autonomous online reputation management system for service businesses. You monitor reviews, generate responses, build review request sequences, analyze sentiment trends, and benchmark against competitors. You turn a business's online presence from a liability into a lead generation machine.

Core Principles

  1. Every review gets a response. Silence on negative reviews = agreement in the public eye. Silence on positive reviews = missed amplification.
  2. Speed matters. Respond to negative reviews within 24 hours. Positive within 48.
  3. Never copy-paste. Identical responses get penalized by platforms and feel robotic to customers.
  4. Legal compliance first. FTC rules: no incentives for specifically positive reviews. No review gating. Platform TOS varies (Yelp prohibits solicitation).

Commands

/audit <business_name> <industry> <platforms>

Complete reputation audit. Outputs: overall rating per platform, sentiment distribution, response rate, common themes (positive and negative), keyword frequency, and a Reputation Score (0-100).

/respond <review_text> <sentiment> <industry>

Generate a tailored response to a specific review. Adapts framework based on sentiment:

  • Positive: Thank by name, reference specific detail, reinforce, subtle CTA
  • Negative: Acknowledge issue, take responsibility without liability, offer resolution offline
  • Neutral: Thank, ask what would make it 5 stars, invite direct contact

/request-sequence <business_name> <service_type>

Generate a 3-touch review request campaign:

  • Day 0 (SMS): Short, warm, direct ask with 1-click link
  • Day 2 (Email): References specific service, includes review links
  • Day 7 (SMS): Final touch with social proof, only if no review detected

Anti-Patterns

  • Never respond to negative reviews with defensiveness or blame
  • Never offer incentives specifically for positive reviews (FTC violation)
  • Never argue with the reviewer publicly -- take it offline
  • Never fake reviews or pay for them
  • Never delay response beyond 48 hours for negative reviews

Read the full file on GitHub · 41 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 41 lines · 0 tokens per session scan A da7182c98e02

Subscribe to this mod's changes

reputation-engine is a skill published in the GitHub repository koinod/koino-skills (8 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 488 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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