report

report is a command for Claude Code from aavaz-ai/enterpret-claude-plugins. It costs 30 tokens per session (4,530 once invoked), scanned A, original, MIT.

A command for turning customer feedback into weekly memos, account briefs, executive summaries, or branded documents. It chooses a report format from your request or lets you select one.

In plain words
What is it for?
Use it to create quick summaries in chat or guided documents with customer quotes, analysis, and citations. It is suited to recurring updates, account reviews, and executive communication.
Why use it?
It removes the need to manually gather feedback, interpret it, and format the result. It also checks that the customer-data connection is set up before starting.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

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

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.

agentmods
npx agentmods add commands/aavaz-ai/enterpret-claude-plugins/report
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 report

README.md
[![agentmods](https://agentmods.dev/badge/commands/aavaz-ai/enterpret-claude-plugins/report.svg)](https://agentmods.dev/commands/aavaz-ai/enterpret-claude-plugins/report)
Your own site
<a href="https://agentmods.dev/commands/aavaz-ai/enterpret-claude-plugins/report"><img src="https://agentmods.dev/badge/commands/aavaz-ai/enterpret-claude-plugins/report.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,530 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00030 $0.04530
Opus 5 $0.00015 $0.02265
Sonnet 5 $0.00006 $0.00906
Haiku 4.5 $0.00003 $0.00453

Measured 5d ago against content hash da7c9eec1bf8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

report 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 5d 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.

commands/report.md · 500 lines

How it starts

The opening of the file, as written. The whole thing — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/report

You are generating a customer intelligence report. This command auto-detects what kind of report to produce based on the input. Quick modes output directly in chat (with optional doc export); document modes follow a guided archetype workflow for branded output.

Pre-Flight

  1. Check if context/organization.json exists. If not, tell the user: "Run /start first to connect to your organization's Knowledge Graph." Stop.
  2. Call get_organization_details from the enterpret-wisdom-mcp MCP server.
  3. If it fails with an auth error, tell the user to run /start and stop.
  4. If successful, read context/organization.json for org name, slug, and citation base URL.

Skills (reference during execution, not upfront)

  • User context is loaded from .local.md in Pre-Flight; defaults are in the wisdom-kg skill
  • wisdom-kg — read if you need schema details or a query fails
  • report-engine — read if user requests formatted document output
  • evidence-synthesis — read when synthesizing quotes and writing the narrative

Query Rules (critical)

  • Always use LIMIT (max 50)
  • Count with COUNT(DISTINCT fi.feedback_record_id) — never COUNT(nli)
  • Never use count as an alias (reserved word) — use volume
  • Sentiment values are capitalized: "Positive", "Negative", "Neutral"
  • Dates use string comparison on record_timestamp: >= "2026-02-27" (not date())
  • Parameter name for execute_cypher_query is cypher_query
  • Never use MATCH after WITH — use a single MATCH with multiple paths
  • If no results, say so — never fabricate data

Phase 0: Mode Detection

Parse the user's command and detect mode:

Quick Modes (chat output first, offer doc export after)

  • /report or /report weekly or /report pmWeekly Memo mode
  • /report Acme Corp or /report canvaAccount Brief mode
  • /report exec or /report leadershipExecutive Summary mode
  • /report US or /report KRRegional Digest mode
  • /report cpo or /report eng or /report cxWeekly Memo mode with audience targeting

Read the full file on GitHub · 500 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. 5d ago First seen · 500 lines · 30 tokens per session scan A da7c9eec1bf8

Subscribe to this mod's changes

report is a command published in the GitHub repository aavaz-ai/enterpret-claude-plugins (2 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 4,530 once invoked, about $0.0002 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.