Trade execution using price action setups, major trend reversal trading top and bottom, MTR failure continuation, strong bull and bear breakout trading, strong and weak channel trading strategies…

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Trade Execution

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill trade-execution -a claude-code

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

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence trade-execution --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/technical-analysis/skills/agentii/trade-execution .claude/skills/trade-execution && 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
trade-execution
GitHub stars
207
Token cost
~2.2k tokens
SKILL.md length
953 words
Files
4 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

Trade execution using price action setups, major trend reversal trading top and bottom, MTR failure continuation, strong bull and bear breakout trading, strong and weak channel trading strategies…

  • Works in 5 steps: Macro Context (degrade-gracefully) → Thesis Input → Setup Selection via MCP (framework-guided) → …
  • Tasks that involve Trading and backtesting
  • SKILL.md covers Defaults, Preflight, Data Source Priority and Methodology, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Trade Execution is an agent skill from agentii-ai/agentii-investment-intelligence. Trade execution using price action setups, major trend reversal trading top and bottom, MTR failure continuation, strong bull and bear breakout trading, strong and weak channel trading strategies, trading range strategies, opening range swings, integration with gold.technicalsetups for setup matching and execution planning

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/execution-scenarios.md`, `references/knowledge-frameworks.md` and `references/modes.md`).

It sits in Business, Finance & HR, covering Trading and backtesting. 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

  • Tasks that involve Trading and backtesting

Example prompts

  • “/trade-execution”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Macro Context (degrade-gracefully)
  2. Thesis Input
  3. Setup Selection via MCP (framework-guided)
  4. Execution Plan Construction
  5. Trade Plan Output

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

Trade Execution loads about 2.2k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 953 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.4k

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). 953 words, ~2,244 tokens.

Download SKILL.mdSave it as .claude/skills/trade-execution/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
trade-execution
description
Trade execution using price action setups, major trend reversal trading top and bottom, MTR failure continuation, strong bull and bear breakout trading, strong and weak channel trading strategies, trading range strategies, opening range swings, integration with gold.technical_setups for setup matching and execution planning
multi_ticker_semantics
single_target
temporal_scope.default_quarters
1
temporal_scope.max_quarters
4
temporal_scope.description
Technical trade execution operates on price data; 1 quarter default.
retrieval_scope
structured_only
layer_tags
L4
min_tool_diversity
2
parameter_free
false

Methodology inspired by publicly taught price action trading frameworks; all text is an original paraphrase.

Defaults

ParameterDefault ValueRationale
swing_reward_min2x riskSwing trades require minimum 2:1 reward-to-risk
scalp_reward1x riskScalp trades take profits at 1:1 reward-to-risk
default_position_risk1-2% of capitalStandard risk per trade
mtr_failure_priorityhighestMTR failure is the strongest continuation signal

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. Trade execution framework — references/execution-scenarios.md (bundled full execution methodology)
  2. Pattern context — from chart-patterns skill output (pattern_type, market_condition, timeframe)
  3. Market structure — from price-action skill output (Always In direction, trend strength)
  4. Technical setups — search_technical_setups + get_technical_setup for exact entry/exit parameters from gold.technical_setups

Methodology

Retrieval Scope

structured_only

Retrieval Strategy

This skill follows Branch (d) Simple Lookup from contracts/retrieval.md: the execution framework is bundled in references/execution-scenarios.md. Real-time price data via get_realtime_quote. Matched technical setups via search_technical_setups and get_technical_setup for detailed execution parameters. No unstructured document retrieval.

Temporal Scope

See frontmatter temporal_scope block.

Tool Allowlist

See frontmatter allowed_tools.

Protocol

This skill implements the price action trading trade execution framework: 12 distinct trading scenarios with specific entry, stop, target, and invalidation rules. The core insight: MTR failures produce the strongest continuation signals. Detailed methodology, setup-specific rules, and the full setup→strategy matrix are in references/execution-scenarios.md.

This skill follows the Mode C (Execution-Focused) retrieval arc per spec 039 Part V.

Step 1 — Macro Context (degrade-gracefully)
  1. Query get_realtime_quote for broad market proxy to assess VIX.
  2. VIX > 25 → tighten position sizing (0.5-1% risk per trade), favor defined-risk setups.
  3. VIX < 15 → standard sizing (1-2% risk per trade).
  4. Macro regime from upstream analysis: expansion favors long setups, contraction favors shorts.
Step 2 — Thesis Input

Receive directional thesis from upstream skills:

  1. From price-action: Always In direction, market condition, trend strength.
  2. From chart-patterns: Primary pattern type, pattern confidence, secondary patterns.
  3. Optional: user-provided thesis direction from fundamental analysis (L2+3 skills).
  4. Conflict resolution: If fundamental thesis conflicts with technical structure, note the divergence and flag for review. Technical structure takes precedence for entry timing.
Step 3 — Setup Selection via MCP (framework-guided)

Match the identified pattern and market condition against gold.technical_setups:

search_technical_setups(
  pattern_type=<pullback|breakout|reversal|trend_following|range_trading>,
  market_condition=<trending_up|trending_down|ranging>,
  timeframe=<derived from time horizon>,
  instrument_scope=[<equity|option|futures>]
)
  1. Filter and rank: Sort by research_score descending. Higher score = more thoroughly researched setup.
  2. Load full setup: get_technical_setup(setup_id=<best_match>) to retrieve complete rules.
  3. Validate against context: Does the setup's market_condition and pattern_type match the current analysis?
  4. Fallback: If no matching setup, use manual execution rules from references/execution-scenarios.md. Flag as coverage_gap.
Step 4 — Execution Plan Construction

Build a complete trade plan by merging methodology with the matched setup's parameters.

Entry specification:

  • Exact entry trigger: e.g., "Buy stop at $X (1 tick above signal bar high)"
  • Alternative entry: e.g., "Or buy market if next bar confirms with strong close"
  • MTR failure special case: "Enter market immediately on break back through trend line"

Stop placement:

  • Primary rule: 1 tick beyond the opposite extreme of the signal bar
  • MTR trades: beyond the most recent swing high/low
  • Breakout trades: below/above the breakout point
  • Adjust stop width to position size: wider stop = smaller size

Profit targets:

  • Scalp target 1: 1x risk → partial position exit
  • Swing target 2: 2x risk or measured move projection → remaining position exit
  • Trailing stop: move stop to breakeven after scalp target reached

Position sizing:

  • Risk per trade = account_risk_pct × capital
  • Position size = risk_per_trade / (entry - stop)
  • Adjust for VIX: higher VIX → smaller size
  • Adjust for setup confidence: higher research_score → larger size (within limits)

Invalidation conditions:

  • Price closes beyond stop before entry triggers
  • Signal bar extreme is violated before the entry bar confirms
  • Market context changes (trend breaks, TR forms) before entry
  • MTR failure: price resumes reversal instead of continuing
Show full SKILL.md (329 more words)Show less
Step 5 — Trade Plan Output

Produce the final executable trade plan:

  1. Setup Summary: Setup name (from MCP), pattern type, confidence level (research_score).
  2. Direction: Long / Short, Always In alignment.
  3. Entry Plan: Exact trigger price, alternative entry method, optimal entry window.
  4. Stop Plan: Exact stop price, stop rationale (which swing point / bar extreme), maximum dollar risk.
  5. Target Plan: Target 1 (scalp) price and size, Target 2 (swing) price and size, trailing methodology.
  6. Position Size: Shares/contracts calculated from risk parameters.
  7. Invalidation: Specific conditions that void the trade before entry.
  8. Post-Entry Management: When to move stop to breakeven, when to trail, when to exit early.

Output File

{ticker}/{YYYY-MM-DD_HHMM}_trade-execution_{affix}.md

Output Structure

  1. Executive Summary — Trade direction, setup name, key price levels, confidence
  2. Context Synthesis — Market structure (price-action), identified pattern (chart-patterns), macro overlay
  3. Setup Selection — MCP search_technical_setups results, selected setup with research_score, match justification
  4. Entry Plan — Exact entry trigger price, alternative entry, execution window, volume conditions
  5. Stop Plan — Exact stop price, stop rationale (which rule applied), maximum dollar/percent risk
  6. Target Plan — Target 1 (scalp) price and percentage of position, Target 2 (swing) price and percentage, measured move reference
  7. Position Sizing — Calculated position size, risk per share, total position risk
  8. Invalidation — Pre-entry invalidation conditions, post-entry stop management rules
  9. Coverage Gaps — Any data limitations, degraded-mode parameters, setup match caveats

Error Handling

ErrorFallback
No matching setup from MCPUse manual execution rules from references/execution-scenarios.md; flag coverage_gap
search_technical_setups unreachableProceed with manual rules only; flag all parameters as manually derived
Pattern confidence lowReduce position size by 50%; flag as lower-confidence trade
Conflicting upstream signalsHold; do not trade. Flag conflict for manual review
No context from upstream skillsDerive market structure from raw price data where possible; flag degraded

Memory Load

See contracts/memory-load.md.

Snapshot

See contracts/snapshot-synthesis.md.

Final Summary (TUI)

Include ### Key Citations block with 0-10 clickable /v/ URLs referencing the matched gold.technical_setups entries.

References

  • references/execution-scenarios.md
  • contracts/citation-and-memory.md
  • contracts/output-frontmatter-schema.md
  • contracts/memory-load.md
  • contracts/snapshot-synthesis.md
  • contracts/preflight.md
  • contracts/retrieval.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/technical-analysis/skills/agentii/trade-execution of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/execution-scenarios.md
  • references/knowledge-frameworks.md
  • references/modes.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Trade Execution 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.

Trade Execution compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Trade Execution this skillagentii-ai/agentii-investment-intelligence207—~2.2kAutomated safety check: PassApache-2.0
Tushare Datazillionare/zillionare3192 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Digital Oraclekomako-workshop/digital-oracle870—~5.9kAutomated safety check: PassMIT
Fintoolsecond-state/fintool3161 repos~5.9kAutomated safety check: PassNone
Polyclawchainstacklabs/polyclaw3601 repos~2kAutomated safety check: PassApache-2.0

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Questions about Trade Execution

What does Trade Execution do?

Trade execution using price action setups, major trend reversal trading top and bottom, MTR failure continuation, strong bull and bear breakout trading, strong and weak channel trading strategies…. Trade Execution is an agent skill from agentii-ai/agentii-investment-intelligence.

When should I use Trade Execution?

Trade Execution fits situations like: tasks that involve Trading and backtesting.

How do I install Trade Execution in Claude Code?

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

How do I install Trade Execution in Codex?

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

Can I use Trade Execution 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 trade-execution -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trade-execution, .gemini/skills/trade-execution, .github/skills/trade-execution and .opencode/skills/trade-execution in your project.

What does Trade Execution need to run?

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

Does Trade Execution 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 Trade Execution 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 Trade Execution use?

Trade Execution 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 Trade Execution use?

About 2.2k tokens (SKILL.md is roughly 9k 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 3.1k tokens, read only when the agent opens those files.

What are the alternatives to Trade Execution?

Skills that share tags, products or a category with Trade Execution: Tushare Data (zillionare/zillionare, 319 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 870 stars) and Fintool (second-state/fintool, 316 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trade Execution?

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.