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industry-research

industry-research is a skill for Claude Code, Codex from 147356/agent-skill-industry-research. It costs 172 tokens per session (4,948 once invoked), scanned A, original, MIT.

An industry-research agent that asks for a brief, researches a chosen market, analyzes the findings, and produces a professional Word document for review.

In plain words
What is it for?
Use it to research a specific industry for investment decisions, startup planning, strategy changes, or general understanding, then deliver the results as a .docx report.
Why use it?
It turns an open-ended research request into a defined scope and a structured report, reducing the need to gather and organize the material manually.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

not rated 4repo 7mo ago A scan 172 tokens original MIT

Good fit Use it to research a specific industry for investment decisions, startup planning, strategy changes, or general understanding, then deliver the results as a .docx report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/147356/agent-skill-industry-research/agent-skill-industry-research
View source ↗ 147356/agent-skill-industry-research
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 147356/agent-skill-industry-research --skill agent-skill-industry-research
Clone the repo
git clone --depth 1 https://github.com/147356/agent-skill-industry-research

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 industry-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/147356/agent-skill-industry-research/agent-skill-industry-research/github.svg)](https://agentmods.dev/skills/147356/agent-skill-industry-research/agent-skill-industry-research)
Your own site
<a href="https://agentmods.dev/skills/147356/agent-skill-industry-research/agent-skill-industry-research"><img src="https://agentmods.dev/badge/skills/147356/agent-skill-industry-research/agent-skill-industry-research/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 industry-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/147356/agent-skill-industry-research/agent-skill-industry-research"><img src="https://agentmods.dev/badge/skills/147356/agent-skill-industry-research/agent-skill-industry-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 172 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,948 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 $0.00172 $0.04948
Opus 5.5 $0.00069 $0.01979
Sonnet 5.5 $0.00034 $0.00990
Haiku 4.5 $0.00017 $0.00495

Measured 2mo ago against content hash bdf0faf76bfe, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

industry-research 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 2mo 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.

SKILL.md · 412 lines

How it starts

The opening of the file, as written. The whole thing — 412 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Industry Research Agent

You are an autonomous industry research agent. Your mission: take a research brief from the user, then independently conduct comprehensive industry research and deliver a professional Word report (.docx).

Workflow Overview

Phase 1: Intake (interactive, 2-3 questions)
    ↓
Phase 2: Autonomous Research (no human input needed)
    ↓
Phase 3: Report Generation (.docx output)
    ↓
Phase 4: Human Review & Revision

Phase 1: Intake (Interactive)

Keep this short and focused. Ask the user these questions (skip any already answered in their initial message):

  1. Target industry — Be specific. If the user says something broad like "AI", ask them to narrow down (e.g., "AI-powered legal document automation for Chinese law firms"). The more specific, the better the research.

  2. Research purpose — This determines emphasis:

    • Investment decision → emphasize market sizing, competitive moats, timing
    • Startup planning → emphasize unmet needs, entry barriers, competitive gaps
    • Strategic pivot → emphasize competitive landscape, trends, risks
    • General understanding → balanced coverage across all dimensions

  3. Research depth — Confirm which level:

    Level Output Autonomous Work
    L1 速览 (Quick Memo) 2-3 page summary Light web research, key facts
    L2 扫描 (Sector Scan) 15-40 page report Thorough web research + user reference materials, data analysis
    L3 深度 (Deep Dive) 40+ page report Exhaustive research, detailed company analysis, full appendices

    Default to L2 unless the user specifies otherwise.

    Note on L2 scope: With sufficient user-provided reference materials (3+ detailed sources), L2 reports routinely expand to 25-40 pages / 30,000-45,000 Chinese characters. This is expected and desirable — do NOT artificially truncate to stay within a page count. Quality and completeness always take priority over page targets.

  4. Any existing context? — Ask if they have files, prior research, or specific companies/data they want incorporated. Absorb these before starting.

Read the full file on GitHub · 412 lines

Files

What ships with it

3 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. 2mo ago First seen · 412 lines · 172 tokens per session scan A bdf0faf76bfe

Subscribe to this mod's changes

industry-research is a skill published in the GitHub repository 147356/agent-skill-industry-research (4 stars, last pushed 7mo ago), licensed MIT. It adds 172 tokens to every session and 4,948 once invoked, about $0.0007 per session on Opus 5.5. 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.

DocumentsResearch
Related

industry-research compared with skills from other repositories

industry-research next to 6 skills from other repositories
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