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show_anti_portfolio

Evaluate sell decisions by tracking post-exit performance of fully sold positions. Shows price change and labels like missed_rebound or good_call.

Instructions

Track the post-exit performance of positions the user has fully sold — the data brokerage apps deliberately don't show (because it would highlight bad sells). For each ticker the user once held but no longer does, returns the last sell date, last sell price, current price, days since exit, post-sell price change %, and a label: missed_rebound (+20% or more since sell — sell was likely premature), good_call (-20% or more — sell saved losses), neutral_exit, or too_recent (<14 days, signal noise). Use when the user is contemplating a sell, reviewing past decisions, or asking 'have my sells worked out?'. Pair with show_thesis_track to connect the original buy thesis to the sell outcome. The summary counts make the user's overall sell discipline visible at a glance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of sold positions to return (most recently sold first).
display_currencyNoDisplay currency (USD/KRW/EUR/JPY/CNY/GBP/HKD/INR/TWD). Defaults to USD.USD
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, description thoroughly explains output and implied read-only nature. Could explicitly state no side effects, but is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is informative but slightly verbose; still well-structured with purpose first, then details and usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without output schema, description fully explains return values, including label conditions. Also covers usage context and pairing, making it complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and both parameters have clear descriptions. Description adds no extra meaning beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool tracks post-exit performance of fully sold positions, with specific metrics and labels. Differentiates from peers like show_thesis_track and show_portfolio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: when contemplating a sell, reviewing past decisions, or asking about sell outcomes. Also suggests pairing with show_thesis_track.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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