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FirmFax prop firm data

get_rule_changes

The dated record of what changed, newest first. Every entry states its KIND, and most of this tape is FirmFax correcting its own data rather than a firm changing its rules. Read counts before describing industry activity: a total taken across kinds overstates it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNofirm = the firm changed a rule. record = FirmFax corrected its own data. withdrawn = we published an entry and then retracted it.
slugNoLimit to one firm. Omit for every firm.
limitNoHow many entries to return, newest first. Default 50.
sinceNoISO date, e.g. "2026-08-01". Entries dated on or after it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers real behavioral context: newest-first ordering, the fact that most entries are FirmFax self-corrections rather than firm rule changes, and a warning that cross-kind totals overstate activity. It omits permission/auth and pagination behavior, keeping it shy of a 5.

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?

Three tightly packed sentences, front-loaded with what the tape is and the ordering, then the kind caveat, then the counting warning. Slightly rhetorical tone but no wasted sentences.

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?

No output schema exists, so the description must convey returns; it does by describing dated entries, ordering, and per-entry KIND. Combined with fully documented params, an agent has enough to call and interpret it, though filter interactions (slug + kind + since combos) are left to the schema.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning for the kind parameter by explaining that the tape is dominated by 'record' corrections and that pooling kinds distorts counts. This tells the agent how to interpret and filter, not just the enum values.

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

Purpose4/5

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

The description clearly frames this as a dated changelog of rule changes, newest first, with each entry tagged by KIND. It distinguishes the tool implicitly from the firm-lookup siblings (get_firm, list_firms) by being a change tape rather than a directory, though it never names an alternative explicitly.

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?

It gives interpretive guidance ('read counts before describing industry activity') but no explicit when-to-use-this-versus-siblings routing, and no prerequisites. Usage is implied by the changelog framing rather than stated.

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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