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Glama

review_positions

Fetch a detailed overview of open positions: thesis, strategy, realized/unrealized P&L, creator activity, and live holdings. Flags overdue checks to help resume an existing Solana meme token plan.

Instructions

The full picture of your open positions, rebuilt from the spreadsheets rather than from anything remembered in this conversation. For each open plan it returns: the written thesis and social evidence recorded at entry, the planned buy/sell strategy, position sizing and realized P&L (from the sheet's formulas), the creator-activity trail, and — read live from chain and the price feed, not the sheet — current holdings, price, and unrealized P&L. Also flags positions whose next-review time has passed. Start here when picking up an existing position; it's the durable memory this connector is built around.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planIdNoReview one plan. Omit to review all open positions.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: data provenance is disclosed ('rebuilt from the spreadsheets rather than anything remembered in this conversation'), live vs. cached is split explicitly (chain/price feed for holdings, price, unrealized P&L; sheet formulas for realized P&L), and the overdue-review flag is surfaced.

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?

Front-loaded with purpose, then a structured enumeration of returned fields, then the routing hint. Dense but every clause earns its place; the 'durable memory' closing line is slightly ornamental but reinforces the mental model.

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

Completeness4/5

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

For a read-only review tool with no annotations and no output schema, the description supplies the essential context: what's returned, where data comes from, and when to reach for it. It does not discuss pagination or response size for the all-positions case, a minor gap.

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 the single planId parameter is already documented in the schema. The description's 'review all open positions' phrasing reinforces the omit semantics but adds no syntax or format detail beyond the schema. Baseline 3 applies.

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?

Precise verb+resource (review open positions) with an explicit scope statement: 'the durable memory this connector is built around.' It clearly distinguishes itself from siblings like get_position (single) and get_plans (plan definitions) before those schemas are even opened.

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

Usage Guidelines4/5

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

Gives a clear when-to-use ('Start here when picking up an existing position') and a scoping mechanism (planId vs. omit for all). It does not explicitly name a sibling or the when-not condition (e.g., versus get_position), so it falls short of a 5.

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