wisdom-slack-digest

wisdom-slack-digest is a skill for Claude Code from aavaz-ai/enterpret-claude-plugins. It costs 99 tokens per session (3,796 once invoked), scanned A, original, MIT.

A workflow for turning customer feedback from Enterpret Wisdom, a customer-information knowledge graph, into a structured digest and delivering it through Slack, email, or the session.

In plain words
What is it for?
Use it for one-off or scheduled customer-feedback summaries with topics, breakdowns, quotes, sentiment, and sources when those settings are configured.
Why use it?
It removes the manual work of gathering feedback, grouping it by topics, formatting a report, and sending it to the intended audience.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the enterpret-customer-insights plugin — 4 skills, 6 commands, 2 agents, 1 hook, 1 MCP server shipped together

Good fit Use it for one-off or scheduled customer-feedback summaries with topics, breakdowns, quotes, sentiment, and sources when those settings are configured.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest
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 aavaz-ai/enterpret-claude-plugins --skill wisdom-slack-digest
Clone the repo
git clone --depth 1 https://github.com/aavaz-ai/enterpret-claude-plugins

Made for: Claude Code.

Or install enterpret-customer-insights, the plugin that ships this one along with the rest of its 4 skills, 6 commands, 2 agents, 1 hook, 1 MCP server.

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 wisdom-slack-digest

README.md
[![agentmods](https://agentmods.dev/badge/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest/github.svg)](https://agentmods.dev/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest)
Your own site
<a href="https://agentmods.dev/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest"><img src="https://agentmods.dev/badge/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest/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 wisdom-slack-digest

Your own site · 80×15
<a href="https://agentmods.dev/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest"><img src="https://agentmods.dev/badge/skills/aavaz-ai/enterpret-claude-plugins/wisdom-slack-digest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,796 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 $0.00099 $0.03796
Opus 5 $0.00049 $0.01898
Sonnet 5 $0.00020 $0.00759
Haiku 4.5 $0.00010 $0.00380

Measured 10d ago against content hash 9e4f850fc643, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

wisdom-slack-digest 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.

skills/wisdom-slack-digest/SKILL.md · 385 lines

How it starts

The opening of the file, as written. The whole thing — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Wisdom Slack Digest — Execution Guide

Generate a structured customer feedback digest from Enterpret's Wisdom Knowledge Graph and deliver it to the user's configured channel. Built for both ad-hoc execution and recurring scheduled delivery via CoWork.

Prerequisites

  • Enterpret Wisdom (enterpret-wisdom-mcp) — the Knowledge Graph server (required)
  • Delivery channel — Slack, email, or other MCP-based connector (optional; CoWork is always available)

Validate Wisdom access before executing. If the configured delivery channel's MCP is unavailable, fall back to displaying the digest in chat and inform the user.

Execution Flow

Step 1: Load configuration

Read context/digest-config.md (in the plugin root). Parse the YAML blocks to extract:

  • digest_title — header for the digest
  • delivery — channel type (slack, email, cowork) and destination (channel ID, address, etc.)
  • topics — list of keyword themes, each with name, keywords, and description
  • breakdowns — dimensions to slice by (if any)
  • display settings — max_quotes_per_topic, max_quote_length, show_sentiment, show_source

If context/digest-config.md does not exist, tell the user to run /digest to set one up. Stop execution.

Step 2: Validate access

Wisdom MCP: Call get_organization_details. If it fails, stop with auth error.

Delivery channel: Check for the configured delivery MCP's tools.

  • If available, proceed normally.
  • If unavailable, switch to CoWork mode (display in chat) and note: "Configured delivery channel ({type}) is not connected. Showing digest in chat instead."

Step 3: Query for each topic

For each topic in the config, build and run a Cypher query. Use the wisdom-kg skill's query rules (LIMIT, count syntax, date formatting).

Topic query — theme-level granularity:

Use search_knowledge_graph first to resolve topic keywords to actual theme names. Then query at the theme level:

MATCH (t:Theme)<-[:HAS_THEME]-(cft:CustomerFeedbackTags)<-[:HAS_TAGS]-(fi:FeedbackInsight)
  -[:HAS_SENTIMENT]->(sp:SentimentPrediction),
  (fi)<-[:SUMMARIZED_BY]-(nli:NaturalLanguageInteraction)
WHERE t.name CONTAINS '{theme_name}'
  AND nli.record_timestamp >= "{start_date}"
RETURN
  t.name AS theme,
  sp.label AS sentiment,
  nli.content AS verbatim,
  nli.source AS source,
  fi.feedback_record_id AS record_id,
  nli.record_timestamp AS timestamp
LIMIT 50

Read the full file on GitHub · 385 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 385 lines · 99 tokens per session scan A 9e4f850fc643

Subscribe to this mod's changes

wisdom-slack-digest is a skill published in the GitHub repository aavaz-ai/enterpret-claude-plugins (2 stars, last pushed 5mo ago), licensed MIT. It adds 99 tokens to every session and 3,796 once invoked, about $0.0005 per session on Opus 5. 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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