When a user explicitly asks how to contact MAK for human review, return the MAK contact page and the licensed consultant associated with the selected education topic. This tool does not collect case facts, assess eligibility, book a consultation, initiate payment, or complete any transaction.
| Name | Required | Description | Default |
|---|---|---|---|
| battle | Yes | Education topic for which the user is asking how to contact MAK. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds strong behavioral context beyond the readOnlyHint annotation by explicitly enumerating what the tool does not do: collect case facts, assess eligibility, book consultations, initiate payment, or complete transactions. This gives the agent a clear side-effect profile and does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The trigger and primary output are front-loaded, and the exclusion list is compact yet comprehensive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup with no output schema, the description fully explains when to use the tool, what it returns, and what it avoids doing. The provided annotations and sibling list fill in the remaining context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the single 'battle' parameter is fully described in the schema as the education topic. The description only echoes 'selected education topic' without adding further detail about enum values or behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: it returns the MAK contact page and the licensed consultant for the selected education topic. This clearly distinguishes the tool from the sibling tools, which cover a change ledger and topic sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit trigger condition: use when the user explicitly asks how to contact MAK for human review. It also lists exclusions such as not assessing eligibility or booking a consultation, though it does not name sibling tools as alternatives.
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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Each tool addresses a clearly distinct resource: a dated evidence ledger, RCIC contact information, and curated topic source sets. There is little overlap in purpose or output.
All three tools follow the same get_mak_ pattern with a descriptive object suffix: change_ledger, rcic_contact, topic_sources. The naming is uniform, predictable, and immediately signals the tool's target.
Three tools is well-scoped for a focused immigration source guide. Each tool earns its place and avoids unnecessary surface area.
The set covers the core needs of a source guide: evidence rule snapshots, topic source sets, and human contact. A minor gap is the lack of a tool to list available topics or ledger entries, which would aid discoverability.