Agent skill

Long Short Equity

by agentii-ai in agentii-ai/agentii-investment-intelligence

long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking…

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Long Short Equity

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill long-short-equity -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence long-short-equity --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/portfolio-strategy/skills/agentii/long-short-equity .claude/skills/long-short-equity && rm -rf skills-src

Use ~/.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/

Facts

Skill name
long-short-equity
GitHub stars
207
Token cost
~1.9k tokens
SKILL.md length
784 words
Files
4 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking…

  • Works in 4 steps: Strategy methodology —… → Strategy frameworks —… → Historical precedent —… → …
  • Business, Finance & HR work in your project
  • SKILL.md covers Defaults, Preflight, Data Source Priority and Methodology, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Long Short Equity is an agent skill from agentii-ai/agentii-investment-intelligence. long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking portfolio construction, long short position management

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/knowledge-frameworks.md`, `references/modes.md` and `references/strategy-methodology.md`).

It sits in Business, Finance & HR. The repository describes itself as: Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered… The licence is Apache-2.0.

When your agent uses it

  • Business, Finance & HR work in your project

Example prompts

  • “/long-short-equity”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Strategy methodology — references/strategy-methodology.md (bundled long/short framework)
  2. Strategy frameworks — search_investment_strategies(domain=fundamental)
  3. Historical precedent — search_investment_cases + search_by_analogue(company_situation=...)
  4. Financials — search_xbrl_facts for unit economics and decline-rate evidence

What it can do on your machine

Read from SKILL.md and the folder at commit 86980e1. 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

Long Short Equity loads about 1.9k tokens when it runs, and up to ~4.6k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 784 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.6k

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 agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 784 words, ~1,935 tokens.

Download SKILL.mdSave it as .claude/skills/long-short-equity/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
long-short-equity
description
long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking portfolio construction, long short position management
multi_ticker_semantics
target_with_optional_peers
temporal_scope.default_quarters
8
temporal_scope.max_quarters
20
temporal_scope.description
8 quarters for portfolio construction; 20 for strategy backtesting.
retrieval_scope
structured_only
layer_tags
L3
min_tool_diversity
4
parameter_free
true

Methodology fused from institutional long/short and buy-side research frameworks; all text is an original paraphrase.

Defaults

ParameterDefault ValueRationale
parameter_freetrueThis skill has no tunable parameters; analysis scope set by temporal_scope frontmatter

Preflight

Run canonical pre-flight per contracts/preflight.md. Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

Data Source Priority

  1. Strategy methodology — references/strategy-methodology.md (bundled long/short framework)
  2. Strategy frameworks — search_investment_strategies(domain=fundamental)
  3. Historical precedent — search_investment_cases + search_by_analogue(company_situation=...)
  4. Financials — search_xbrl_facts for unit economics and decline-rate evidence

Methodology

Retrieval Scope

structured_only

Retrieval Strategy

Ownership & insider signals: search_institutional_holdings (top-10 holders + whale portfolios, direction=accumulating|reducing|new|exited) and search_insider_trades (Form-4 transactions with SEC URLs) are available as signal inputs.

Branch (a) Structured Data Query from contracts/retrieval.md. Retrieve frameworks via search_investment_strategies, precedent via search_investment_cases and search_by_analogue. Detailed methodology in references/strategy-methodology.md.

Temporal Scope

See frontmatter temporal_scope block.

Tool Allowlist

See frontmatter allowed_tools.

Protocol

Every long/short position rests on an earnings disconnect — a gap between what the market has priced and what the business will deliver. The unifying question across all strategy types is: what does consensus believe, and what do I believe differently? Strategy spectrum, short archetypes, and process detail are in references/strategy-methodology.md.

Consensus is not the published number. Sell-side consensus is a simple average of analyst estimates; buy-side consensus typically moves ahead of it. Trading against the published figure while the real positioning has already shifted is a common and expensive error. Triangulate the effective buy-side expectation before sizing any view.

Steps
  1. Strategy Classification: Place the idea on the spectrum from spread-focused to fundamentals-focused — merger arbitrage (0-18mo), general event-driven (0-24mo), activist (0-24mo), value/deep value (0-5yr+), growth or growth-at-reasonable-price (0-5yr+). The classification sets the expected holding period and the evidence bar. Categories overlap; record the dominant driver rather than forcing a single label.

  2. Consensus Reconstruction: Establish the published sell-side figure, then estimate the effective buy-side expectation. Document the gap and its direction — the disconnect is the position, not the absolute valuation level.

  3. Idea Provenance: Record how the idea was sourced — industry research and trade events, tangential analysis of adjacent markets, practitioner conversations, curated research communities, or quantitative screens. Provenance predicts which failure modes to test for: screen-sourced ideas need qualitative validation, conversation-sourced ideas need independent quantitative confirmation.

  4. Long-Side Thesis: Apply value or growth frameworks per classification. Value requires a discount to net present value on a price basis; growth requires a discount on an earnings basis. State which, and why the market has mispriced it.

  5. Short-Side Archetype (when shorting): Classify into one of three patterns — competition short (complacent incumbent facing a credible new entrant; test the entrant's unit economics and assess whether incumbent management can and will react), consumer euphoria (a product with outsized enthusiasm that will not sustain; test via market sizing and product work), or disappearing business (an incumbent in a structurally terminal market; establish the rate of decline, the cash-flow profile during decline, and whether cash can be redeployed). Each archetype has a distinct evidence requirement — do not substitute a valuation opinion for the archetype test.

  6. Precedent Retrieval: Query search_by_analogue for the matching situation and search_investment_cases for outcome history. Weight precedent by archetype match, not sector match.

  7. Risk and Invalidation: Name what would falsify the thesis and by when. For shorts, additionally record borrow availability, short interest, and days-to-cover — a correct short thesis in a crowded, hard-to-borrow name is not an executable position.

  8. Output: Deliver the classification, the quantified disconnect, the archetype evidence, precedent with /v/ citations, and explicit invalidation conditions.

Show full SKILL.md (190 more words)Show less

Output File

{ticker}/{YYYY-MM-DD_HHMM}_long-short-equity_{affix}.md

Output Structure

  1. Executive Summary — strategy classification, the disconnect, and direction in 2-3 sentences
  2. Strategy Classification — position on the spread-to-fundamentals spectrum with expected holding period
  3. Consensus Disconnect — published sell-side figure vs estimated buy-side expectation, with the gap quantified
  4. Idea Provenance — sourcing route and the failure modes it implies
  5. Thesis Detail — long-side value/growth basis, or short-side archetype with its specific evidence test
  6. Historical Analogues — archetype-matched precedent with /v/ citations
  7. Executability — for shorts: borrow, short interest, days-to-cover
  8. Risk and Invalidation — falsification conditions and deadline
  9. Coverage Gaps — data limitations and degraded flags

Error Handling

ErrorFallback
No strategy frameworks availableProceed with references/strategy-methodology.md; flag knowledge_coverage: degraded
Buy-side consensus cannot be triangulatedReport the sell-side figure only and mark the disconnect as unquantified
Borrow / short-interest data unavailableMark the short as not executability-cleared; do not present it as actionable
search_by_analogue returns emptyContinue without precedent; annotate coverage_gap

Final Summary (TUI)

Include ### Key Citations block (0–10 /v/ URLs).

Memory Load

Load prior context before retrieval. See contracts/memory-load.md.

Snapshot

Post-session synthesis. See contracts/snapshot-synthesis.md.

Output Frontmatter

Structured output per contracts/output-frontmatter-schema.md.

References

  • references/strategy-methodology.md
  • references/knowledge-frameworks.md
  • contracts/citation-and-memory.md
  • contracts/retrieval.md
  • contracts/preflight.md

© agentii-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 3 other files (references) in plugins/vertical-plugins/portfolio-strategy/skills/agentii/long-short-equity of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/knowledge-frameworks.md
  • references/modes.md
  • references/strategy-methodology.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Long Short Equity 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.

Long Short Equity compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Long Short Equity this skillagentii-ai/agentii-investment-intelligence207—~1.9kAutomated safety check: PassApache-2.0
Technical Analysttradermonty/claude-trading-skills3k4 repos~4.6kAutomated safety check: PassMIT
Theme Detectortradermonty/claude-trading-skills3k2 repos~4.9kAutomated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7293 repos~1.3kAutomated safety check: PassMIT
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT
Itr Walakaranb192/itr-wala871—~3.6kAutomated safety check: PassMIT

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Questions about Long Short Equity

What does Long Short Equity do?

long short equity strategy, pair trade construction, market neutral portfolio, net exposure management, factor neutrality, equity long short, hedge fund strategy, alpha generation, stock picking…. Long Short Equity is an agent skill from agentii-ai/agentii-investment-intelligence.

When should I use Long Short Equity?

Long Short Equity fits situations like: business, Finance & HR work in your project.

How do I install Long Short Equity in Claude Code?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill long-short-equity -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/portfolio-strategy/skills/agentii/long-short-equity in agentii-ai/agentii-investment-intelligence) into .claude/skills/long-short-equity in your project. Claude Code loads it when a task matches its description.

How do I install Long Short Equity in Codex?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill long-short-equity -a codex`. Or copy the skill folder (plugins/vertical-plugins/portfolio-strategy/skills/agentii/long-short-equity in agentii-ai/agentii-investment-intelligence) into .agents/skills/long-short-equity in your project. Codex loads it when a task matches its description.

Can I use Long Short Equity 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 agentii-ai/agentii-investment-intelligence --skill long-short-equity -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/long-short-equity, .gemini/skills/long-short-equity, .github/skills/long-short-equity and .opencode/skills/long-short-equity in your project.

What does Long Short Equity need to run?

SKILL.md names no scripts, command-line tools or credentials: Long Short Equity is instructions for the agent only.

Does Long Short Equity 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 Long Short Equity 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 Long Short Equity use?

Long Short Equity 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 Long Short Equity use?

About 1.9k tokens (SKILL.md is roughly 7.7k 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 2.7k tokens, read only when the agent opens those files.

What are the alternatives to Long Short Equity?

Skills that share tags, products or a category with Long Short Equity: 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 Long Short Equity?

agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.

Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.