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SwogeAgentic

colony activity

colony_activity
Read-only

What the SWOGE AI colony (an autonomous paper-trading colony on Robinhood Chain that learns from every token it watches) is doing: open positions, latest buys and sells with their results, the real-money mirror record, and its overall paper ledger. Optionally filtered to one token symbol or address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quoteNotrue: return the price of this call without running or paying for it
tokenNooptional token symbol (e.g. TELEPAD) or address to filter on

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the read-only nature. The description adds valuable context by explaining what data is returned (positions, trades, mirror record, ledger) and that it is a paper-trading colony, which informs the agent of the data's nature (simulated, not real-money). This goes beyond the annotations without contradicting them, adding useful behavioral context.

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?

The description is a single sentence that efficiently packs the core purpose and the optional filter. It is front-loaded with the primary content (what the colony is doing) and includes the filter mention at the end. There is no redundancy or filler, though the opening 'What the ... is doing:' is slightly verbose but not detrimental.

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 summary tool with no output schema, the description sufficiently covers what the agent needs to know: it returns colony activity details and can be filtered. It does not specify the exact response format, but given the tool's simple nature and the annotations covering safety, the description is complete enough for correct invocation. A slight gap is the lack of mention of the quote parameter's purpose in the description, but that is already in the schema.

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 description coverage is 100%, with both parameters (quote and token) well-described in the schema. The tool description adds minimal value: it reiterates the optional filter on token but does not introduce new syntax or format details. Since the schema already fully documents the parameters, a baseline score of 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?

The description clearly states the resource (the SWOGE AI colony) and the specific data it exposes: open positions, buys/sells with results, mirror record, and paper ledger. It distinguishes itself from siblings like scan_token or wallet_intel by focusing on colony-level activity rather than individual token or wallet analysis. The optional filter is also mentioned, making the purpose unambiguous.

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

Usage Guidelines3/5

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

The description implies usage (query colony activity) but does not explicitly state when to prefer this over alternatives or mention any exclusions. It lacks guidance like 'use this to see the colony's overall performance' or 'for individual token analysis, use scan_token instead.' The context is clear, but the when-to-use versus not-use is left to inference.

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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