Market Intel

market-intel

Triage a commercial topic across 15 data domains, auto-detect the right specialized source, then delegate the heavy research to the harness you already have.

[](https://docs.anthropic.com/en/docs/claude-code) [](LICENSE) [](skills/market-intel/reference/sources-index.md) [](skills/market-intel/reference/tools/index.md) [](#languages) [](ROADMAP.md)

[English](README.md) | [中文版](README_CN.md)

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⭐ Read this first, the design philosophy

market-intel is built on one principle, root-cause design, not incremental patching. When something is wrong, we change the assumption underneath it, not the symptom on top. That single idea produced every decision here: browser-automation was promoted from footnote to a first-class route (not "add a few free tools"); this is a thin delegation layer (not "another deep-research"); updates run through a deterministic gate that can only let the matrix improve (not "set a reminder to refresh"). The philosophy outranks any individual feature, every future change must pass one test: does it fix the framing, or just patch a symptom?

📜 [Read the full design philosophy → PHILOSOPHY.md](PHILOSOPHY.md) (6 principles, each with the patch-vs-root contrast and the real decision in this repo that it produced).

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What it is (and isn't)

Claude Code already has a deep-research harness (fan-out → fetch → verify → synthesize) and a research-lit skill. Those are great for general web and academic research. They fall short the moment your question needs a specialized commercial source behind an information barrier, real X/Twitter data, Amazon price history, on-chain feeds, SEO metrics, social sentiment, B2B lead data.

market-intel is the thin layer that fills exactly that gap. It does only three things nothing else does, and delegates everything else:

1. Triage, map a commercial topic to 1 to N of 15 data domains.
2. Detect + guide install, check which specialized MCP sources are actually connected (via claude mcp list, not unreliable tool-name guessing), and if a key source is missing, hand you the exact claude mcp add command, or open its per-tool how-to doc ([reference/tools/](skills/market-intel/reference/tools/index.md)) for install + auth + usage + gotchas, guided by a multi-level [install guide](skills/market-intel/reference/install-guide.md).
3. Quality guardrails, citation verification, source tiers, multi-source corroboration, mandatory disconfirmation, explicit gaps.

The actual fan-out, fetching, adversarial verification, and citation synthesis are delegated to deep-research / research-lit. No reinvented engine, no trigger fights.

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Install

/plugin install github:DaizeDong/market-intel

Or clone manually:

git clone https://github.com/DaizeDong/market-intel.git ~/.claude/plugins/market-intel

It auto-activates on phrases like 市场调研, competitor analysis, research this market, find arbitrage opportunities, X/Twitter sentiment, SEO intel, product trends. For single-fact lookups or general web reports it deliberately steps aside (use plain search / deep-research); for academic literature it defers to research-lit.

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Config

market-intel is config-bearing, it reads per-user state (keys, installed-tool registry) from a separate, private companion config repo. Repo-root contract: [CONFIG.md](CONFIG.md); authoritative deep spec: [companion-config-spec.md](skills/market-intel/reference/companion-config-spec.md) (v1.3, STABLE).

• Mount (discovery order): $MARKET_INTEL_CONFIG → ~/.market-intel-config/ →

~/.config/market-intel-config/. First that exists wins; absent = runs in matrix-only mode.

• First time:

``bash python scripts/init_config.py # stamp a conformant skeleton (deterministic) export MARKET_INTEL_CONFIG=~/.market-intel-config # or pass --out to init python scripts/verify_config.py # doctor: PASS/FAIL, names what is missing ``

• Switch configs (hot-swap): point the env var at another config dir, configs are self-contained,

no other change needed: export MARKET_INTEL_CONFIG=~/configs/work ↔ ~/configs/personal.

• Secrets: Mode B, the companion repo is separate and private; secrets/* is gitignored and never

enters git; back up out-of-band.

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Quick start, install the free no-key bootstrap pack (3 minutes)

Want to try it without configuring API keys? Install these 3 free, no-key MCPs first, they cover HN/Reddit-style community + market trends + AI papers at zero cost:

# 1. Hacker News (community)
claude mcp add -s user mcp-hn 'uvx mcp-hn'

# 2. GDELT (global news + trends, no key)
claude mcp add -s user gdelt 'uvx gdelt-mcp'

# 3. arXiv (research papers, no key)
claude mcp add -s user arxiv 'uvx arxiv-mcp-server'

Then restart the Claude session (claude → re-enter; MCPs only register on session start).

Now ask: 调研一下 AI agent 工具生态的趋势. The skill will fan out research subagents that use these three sources together, community signal + trends + papers, and produce a sourced report. No keys, no signup, ~30s start-to-first-finding.

After this, the [60-second tour](#60-second-tour) below explains the specialized MCPs (paid X data, Bright Data, Keepa, etc.), these unlock the high-quality routes the skill is really designed for.

Now what?, installed it, what do I read first?

Three different "next steps" depending on intent. Pick one:

| If you want to… | Open this | |---|---| | Use the skill (just have it trigger automatically and run research for you) | Nothing else, the skill is loaded; type a research query. | | Install your first specialized MCP (e.g. a real X data source, a finance API) | skills/market-intel/reference/install-guide.md, L0 install mechanics; then skills/market-intel/reference/tools/.md for the specific tool you picked from the source matrix below. | | Set up a private companion config repo to persist your install state + secrets across machines (recommended for >1 tool) | skills/market-intel/reference/companion-config-repo.md, overview + tutorial. Then companion-config-spec.md (formal contract) and companion-config-hardening.md (GitHub-side lockdown BEFORE first push). |

Most users want path 2 first, then path 3 once they accumulate >1 tool / >1 machine.

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60-second tour

You say:

research the competitive landscape and X sentiment around , then find any arbitrage angle

What runs:

1. Triage → maps to x-twitter, trends-discovery, ecommerce-arbitrage; picks a depth budget with hard caps (no runaway fan-out).
2. Detect → runs claude mcp list, sees you have none of the X/ecommerce MCPs connected, notes it.
3. Guide install (non-blocking) → "This depends on real X data. Install twitterapi.io: claude mcp add -s user ..., note it only works after a session reconnect. For now I'll use web fallback and flag the gap."
4. Delegate → fans out subagents / invokes deep-research, each returning a structured evidence unit (claim · source · quote · tier · date · confidence), not raw page dumps.
5. Guardrails → independent verifier re-fetches each cited URL; decision-grade claims need ≥2 independent sources; a dedicated reverse-search subagent hunts risks/failures.
6. Report → snapshot-dated, tier-tagged, with a disagreement matrix, a mandatory Risks & counter-evidence section, and an explicit "configure source X for deeper data" gap list.

Try one of these as your first real query

After the Quick Start install, try invoking the skill on something concrete:

• 调研一下 AI agent 工具生态最近一个月的趋势, exercises trends + community + frontier-research
• compare the top 3 hosted MCP marketplaces (Smithery / Glama / PulseMCP) — coverage, pricing, signal-to-noise, exercises mcp-ecosystem
• find me 3 underrated open-source web-scraping tools released in 2026 with > 200 stars, exercises web-scraping + GitHub velocity discovery
• who's been launching credible LLM eval skills in the last 3 months, exercises ready-skills + frontier-research

Each will fan out subagents, surface evidence with citations, and end with a "gaps if you connect source" list. If a query produces only web-fallback output, that's the skill being honest about its coverage, see the install-guide to add a specialized MCP for deeper data.

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Skills at a glance

The source matrix (15 domains)

The knowledge asset. Each domain shard names the best tool, its barrier route, how to detect it, and what to install. Thin index → load only the domain(s) you need. Each tool also has a per-tool how-to doc under [reference/tools/](skills/market-intel/reference/tools/index.md) (install + auth + usage + 踩坑), reached on-demand via the thin tool index.

| Domain | Top pick (barrier route) | |---|---| | [x-twitter](skills/market-intel/reference/domains/x-twitter.md) | twikit ④③ · twitterapi.io ② resale | | [reddit-community](skills/market-intel/reference/domains/reddit-community.md) | HN MCP ① free · reddit-mcp-buddy ① | | [web-scraping](skills/market-intel/reference/domains/web-scraping.md) | Tavily/Exa + Firecrawl + Bright Data | | [ecommerce-arbitrage](skills/market-intel/reference/domains/ecommerce-arbitrage.md) | Keepa ① official (seller-side) | | [finance-markets](skills/market-intel/reference/domains/finance-markets.md) | SEC EDGAR + FRED ① free | | [crypto-defi](skills/market-intel/reference/domains/crypto-defi.md) | CoinGecko ① + ccxt | | [seo-keywords](skills/market-intel/reference/domains/seo-keywords.md) | GSC ① free + DataForSEO ② | | [social-publishing](skills/market-intel/reference/domains/social-publishing.md) | Buffer ① · Postiz OSS | | [content-cms](skills/market-intel/reference/domains/content-cms.md) | Sanity / WordPress MCP ① | | [leadgen-crm](skills/market-intel/reference/domains/leadgen-crm.md) | Apollo.io ① + Hunter ① | | [trends-discovery](skills/market-intel/reference/domains/trends-discovery.md) | GDELT + Product Hunt MCP ① free | | [frontier-research](skills/market-intel/reference/domains/frontier-research.md) | arXiv API + HF Daily Papers ① free | | [ready-skills](skills/market-intel/reference/domains/ready-skills.md) | coreyhaines31/marketingskills | | [browser-automation](skills/market-intel/reference/domains/browser-automation.md) | playwright MCP + browser-use / crawl4ai ④ | | [consumer-price-compare](skills/market-intel/reference/domains/consumer-price-compare.md) | delegates to sister skill shopping-aggregator |

Barrier routes: ① official API (compliant, often paid) · ② resale API (provider absorbs the barrier, cheap, gray-area) · ③ self-host scrape (reverse-engineered API, free, accounts+proxies, ban risk) · ④ browser automation / act-like-human, real logged-in browser (playwright MCP + free OSS repos). First-class, not a footnote: often returns richer data (rendered/logged-in view, fields APIs hide) at zero API cost. The skill prefers route ④ over paid APIs when it fits, reaching for ①/② only for history it can't backfill (e.g. Keepa), scale reliability, or compliance.

Three install levels: [install-guide.md](skills/market-intel/reference/install-guide.md) (L0 mechanics) → [pricing-install.md](skills/market-intel/reference/volatile/pricing-install.md) (L1 per-domain commands + prices, last_verified-stamped) → [tools/.md](skills/market-intel/reference/tools/index.md) (L2 per-tool). Verify volatile prices against the official site before quoting.

Sister skill, consumer-side specialization

For consumer shopping price comparison (Amazon / eBay / Walmart / Target / Taobao / JD price compare + Keepa / Camelcamelcamel / 慢慢买 history + Capital One Shopping / Karma / 购物党 coupons + Honey 2026 trust event), market-intel defers to its sister skill: shopping-aggregator. market-intel handles broad commercial research + seller-side ecommerce-arbitrage; shopping-aggregator handles the consumer buy decision. Both skills can coexist, see [consumer-price-compare shard](skills/market-intel/reference/domains/consumer-price-compare.md) for the routing logic.

/plugin install github:DaizeDong/shopping-aggregator

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How to invoke

It auto-activates on phrases like 市场调研, competitor analysis, research this market, find arbitrage opportunities, X/Twitter sentiment, SEO intel, product trends, 调研这个市场, 竞品分析, 找套利机会, X/推特舆情, SEO 情报, 产品趋势. To refresh the source matrix, say 刷新工具库 / refresh the market-intel source matrix.

It deliberately steps aside for single-fact lookups or general web reports (use plain search / deep-research) and defers academic literature to research-lit.

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Example output

A finished run is snapshot-dated, tier-tagged, and built from structured evidence units (claim · source · quote · tier · date · confidence) rather than raw page dumps:

• Decision-grade claims carry ≥2 independent sources, each tagged confidence high/medium/low.
• A disagreement matrix surfaces conflicts instead of averaging them.
• A mandatory Risks & counter-evidence section (a reverse-search subagent hunts scam/failure/risk).
• An explicit "configure source X for deeper data" gap list where coverage fell back to web.

See the [60-second tour](#60-second-tour) for the step-by-step of what produces this.

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Quality guardrails

Hard rules applied during synthesis (see [SKILL.md](skills/market-intel/SKILL.md)):

• Citation verification gate, an independent verifier re-fetches every cited URL and confirms the page contains the value (verbatim quote). Dead links dropped; quote-less numbers demoted to "unverified."
• ≥2 independent sources for decision-grade claims; each tagged confidence high/medium/low.
• Source tiers L1 first-party → L5 fallback/inference; vendor self-claims can't be sole support.
• No silent degradation, falling back from a barrier source to web is flagged in-line.
• Timestamp volatile data, every price/policy carries fetched + published dates.
• Disconfirmation mandate, a reverse-search subagent hunts scam/failure/risk; arbitrage gets an explicit execution-friction section.
• Surface conflicts, don't average them; failures become explicit coverage gaps.

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Limitations

• The matrix decays, APIs go paid, tools get acquired, prices move. The [refresh protocol](skills/market-intel/reference/refresh-protocol.md) re-sweeps each domain (one subagent per domain → structured diff → incremental shard edits → CHANGELOG.md + version bump). Default cadence is monthly (v0.17.0); weekly for the fast-moving set (crypto-defi, browser-automation, frontier-research, mcp-ecosystem); quarterly is reserved for the Horizon scan (cross-domain new-territory discovery). Trigger manually with 刷新工具库 / refresh the market-intel source matrix, or wire a scheduled headless run (see [ROADMAP](ROADMAP.md)).
• Web fallback is honest, not magic, if no specialized MCP is connected, the skill says so and flags the gap rather than pretending the web answer is as deep.
• No reinvented engine, the fan-out/verify/synthesize depth is delegated to deep-research / research-lit; market-intel is the routing + detection + guardrail seam, not a research engine of its own.

This skill is the product of a 12-subagent tool survey followed by a 5-subagent adversarial design review. The review killed the original "build another full deep-research" plan (it would have been a clone with a trigger conflict), proved that claude mcp add doesn't take effect until a session reconnect, and forced in the citation-verification gate, source tiers, and disconfirmation mandate.

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Languages

English (README.md, authoritative) · 中文 ([README_CN.md](README_CN.md)).

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Roadmap · Contributing · License

See [ROADMAP.md](ROADMAP.md) · [CONTRIBUTING.md](CONTRIBU

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: DaizeDong
• Source: DaizeDong/market-intel
• License: MIT

Install and usage instructions live in the source repository linked above.