Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses.
Install Sector Overview
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ginlix-ai/LangAlpha sector-overview --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .claude/skills/sector-overview && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .claude/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ginlix-ai/LangAlpha sector-overview --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .agents/skills/sector-overview && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .agents/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ginlix-ai/LangAlpha sector-overview --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .cursor/skills/sector-overview && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .cursor/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ginlix-ai/LangAlpha.git --path plugins/langalpha_research/skills/sector-overview--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ginlix-ai/LangAlpha sector-overview --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .gemini/skills/sector-overview && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .gemini/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ginlix-ai/LangAlpha sector-overviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .github/skills/sector-overview && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .github/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ginlix-ai/LangAlpha --skill sector-overview -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ginlix-ai/LangAlpha sector-overview --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/langalpha_research/skills/sector-overview .opencode/skills/sector-overview && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sector-overview" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/sector-overview into .opencode/skills/sector-overview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sector-overview", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sector-overview- GitHub stars
- 1.8k
- Token cost
- ~2k tokens
- SKILL.md length
- 1,145 words
- Files
- 5 (incl. references)
- Skills in repo
- 37
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses.
- Works in 7 steps: Scope it → Classify into an archetype before… → Size the market, and say which kind of… → …
- Sector overview
- SKILL.md covers Workflow and Important notes
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Sector Overview is an agent skill from ginlix-ai/LangAlpha. Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses. Triggers on sector overview, industry landscape, industry primer, sector deep dive, market map.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/sectors/README.md`, `references/sectors/banks.md` and `references/sectors/energy.md`).
It sits in Business, Finance & HR. The repository describes itself as: Claude Code for Financial Market. The licence is Apache-2.0.
When your agent uses it
- Sector overview
- Industry landscape
- Industry primer
- Sector deep dive
Example prompts
- “/sector-overview”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 2855e43. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sector Overview loads about 2k tokens when it runs, and up to ~7.5k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 1,145 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from ginlix-ai/LangAlpha at commit 2855e43, republished under its Apache-2.0 licence (© ginlix-ai). 1,145 words, ~1,994 tokens.
Download SKILL.mdSave it as
.claude/skills/sector-overview/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sector-overview
- description
- Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses. Triggers on sector overview, industry landscape, industry primer, sector deep dive, market map.
Sector Overview
A landscape report on an industry: how it earns money, who is winning, what it is worth, and what would change that. The quality of the report is decided in the first step, not the last: a set classified into the wrong archetype produces the right-looking report with the wrong metrics, the wrong multiple and the wrong risks.
Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.
Workflow
1. Scope it
- Sector or subsector, and how narrowly the boundary is drawn.
- Purpose: a client report, a research packet, pitch material, idea generation.
- Angle: a neutral landscape, or a thematic thesis the report is testing.
- Universe: public names only, or private included.
- Depth: default
working analysis; a sector screen is afirst pass. Bands and what to cut first:.agents/skills/research-conventions/references/depth.md.
2. Classify into an archetype before analysing
Write down how each company in the set actually earns money, and put it in an archetype. Business model beats label: two names carrying the same sector tag and different revenue mechanics share no metric set, no valuation lens and no risk list. Classify from the revenue recognition note and the segment note of the largest names in the set, not from the sector tag.
Load the lens for the set before Step 3:
- Software, internet, marketplace or advertising:
.agents/skills/sector-overview/references/sectors/software-and-internet.md. - Banks, lenders and capital-markets firms:
.agents/skills/sector-overview/references/sectors/banks.md. - Producing, moving, refining or selling energy:
.agents/skills/sector-overview/references/sectors/energy.md. - Any other sector, and adding a lens for it:
.agents/skills/sector-overview/references/sectors/README.md.
Every company in the set carries one archetype label before a metric is pulled, and the comparison table in Step 4 is the archetype's metric set rather than a generic one.
3. Size the market, and say which kind of number each figure is
Market size and growth. Current size, historical growth, forecast growth with the assumption behind it, and the segmentation that matters (product, geography, end market, customer type).
Two kinds of figure, labelled on the face of the table:
- Sized: built bottom-up from disclosed units, prices or revenue that can be added up and checked.
- Extrapolated: a growth rate applied to a base someone else sized.
An extrapolated figure supports direction and never carries a conclusion that a sized figure would have to support. A forecast growth rate whose method is not stated is an assumption and is labelled one. State the addressable market the company can actually reach beside the total, and where the two differ, the gap is the interesting number.
Staleness. Sector size and share research stays fresh for twelve months and always prints its vintage; every sized figure carries its as-of in the table, not in a footnote at the end. A study past twelve months either gets refreshed or gets a line saying what has changed since it was published. Thresholds by data type and the six staleness states: .agents/skills/research-conventions/references/evidence.md.
Structure and drivers. Fragmented or consolidated, with the top-five share and its source. The value chain, and where in it the margin actually sits. Barriers to entry (capital, regulatory, technical, network). Three to five secular drivers, the headwinds against them, the technology and regulatory vectors, and the consolidation pattern.
4. Map the competitive landscape
Profile the top five to ten names on the archetype's metrics, not on a generic revenue and margin table:
| Company | Archetype | [KPI 1] | [KPI 2] | [KPI 3] | Share | As-of | Label |
|---|
Each name also gets a short profile: what it does in two sentences, where it is positioned and why that holds, what changed recently, and a valuation snapshot on the sector's lead lens. Then the dynamics: how the companies compete, who is gaining and losing share and through which mechanism, and where the disruption comes from.
Row-merge discipline. The rule for sharing a row in an exposure or driver table is in .agents/skills/research-conventions/references/judgment.md. In a sector table its common failure is thematic adjacency: two companies reached by the same theme through different line items look mergeable and are two rows.
Show full SKILL.md (484 more words)Show less
5. Value the sector in its own lens order
Lead with the first lens from the sector file, and say in one sentence which generic lens is wrong here and why, so the omission reads as a choice.
The wrong-lens failure. A revenue-growth-and-margin frame applied to a bank, an insurer or a REIT produces an answer that is confident, internally consistent and wrong: a bank's debt is raw material rather than financing, an insurer's earnings are a reserve estimate, and a REIT's reported earnings are rents suppressed by depreciation. One sentence before the valuation section is written settles it: what is this sector's multiple a function of? When the answer is not the lens on the page, the lens is the thing to change.
Then the sector context: current multiples against their own historical range, what drives the premium or discount across the set, recent transaction multiples with the basis stated, and how the sector prices against the broader market. Every multiple carries its as-of, its LTM or NTM label and one common base date across the table: .agents/skills/research-conventions/references/market-data-rules.md.
6. Draw the implications, and separate the orders of effect
Where the report turns on a shock (a rate move, a tariff, an input-cost move, a regulation), report the orders of effect in separate rows at separate confidence rather than blended into one conclusion:
- Direct: names the transmission channel and the line item it lands on.
- Second order: names whose behaviour has to change in between.
- Third order: the competitive or structural response, at the lowest confidence and often past the horizon.
When the channel cannot be named, the claim is not ready to write and the next step is source work rather than prose. The full rule, with the action vocabulary and the falsifiable-claims table: .agents/skills/research-conventions/references/judgment.md.
Close on where the risk and reward sit, which thematic bets the sector can express, the two or three live debates stated at their strongest on both sides, and the dated catalysts that would settle them.
7. Build the deliverable
A document or a deck carrying one readiness posture stated once near the top, the market overview and sizing, the landscape map, the comparison table, the valuation summary, and the charts that do the work: market growth, share trend, and a valuation scatter on the sector's lead lens. A workbook appendix carries the company data behind the tables.
Format is owned by the deliverable skill: .agents/skills/docx/SKILL.md, .agents/skills/pptx/SKILL.md, .agents/skills/xlsx/SKILL.md.
Important notes
- Charts carry this report. A sizing waterfall, a positioning map and a valuation scatter say in one look what three paragraphs say slowly.
- Where the reader has a specific situation (a target list, a market-entry question, a positioning problem), the "so what" section is written to that situation rather than to the sector in general.
- A sector report with no view is a directory. Name which archetype the structure favours over the horizon, and what would reverse it.
© ginlix-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (references) in plugins/langalpha_research/skills/sector-overview of ginlix-ai/LangAlpha.
- SKILL.md
- references/sectors/README.md
- references/sectors/banks.md
- references/sectors/energy.md
- references/sectors/software-and-internet.md
Open the folder on GitHubat commit 2855e43
Compare with similar skills
Sector Overview next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sector Overview this skillginlix-ai/LangAlpha | 1.8k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Sector Overview
What does Sector Overview do?
Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses. Sector Overview is an agent skill from ginlix-ai/LangAlpha. Sector and industry landscape report, built on the sector's own archetypes, metrics and valuation lenses.
When should I use Sector Overview?
Sector Overview fits situations like: sector overview; industry landscape; industry primer; sector deep dive.
How do I install Sector Overview in Claude Code?
Run `npx skills add ginlix-ai/LangAlpha --skill sector-overview -a claude-code`. Or copy the skill folder (plugins/langalpha_research/skills/sector-overview in ginlix-ai/LangAlpha) into .claude/skills/sector-overview in your project. Claude Code loads it when a task matches its description.
How do I install Sector Overview in Codex?
Run `npx skills add ginlix-ai/LangAlpha --skill sector-overview -a codex`. Or copy the skill folder (plugins/langalpha_research/skills/sector-overview in ginlix-ai/LangAlpha) into .agents/skills/sector-overview in your project. Codex loads it when a task matches its description.
Can I use Sector Overview in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ginlix-ai/LangAlpha --skill sector-overview -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sector-overview, .gemini/skills/sector-overview, .github/skills/sector-overview and .opencode/skills/sector-overview in your project.
What does Sector Overview need to run?
SKILL.md names no scripts, command-line tools or credentials: Sector Overview is instructions for the agent only.
Does Sector Overview access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Sector Overview safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Sector Overview use?
Sector Overview is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sector Overview use?
About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.5k tokens, read only when the agent opens those files.
What are the alternatives to Sector Overview?
Skills that share tags, products or a category with Sector Overview: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sector Overview?
ginlix-ai (a GitHub organization) maintains it in ginlix-ai/LangAlpha, which has 1,811 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 10, 2026.
Source: ginlix-ai/LangAlpha on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.