get_recent_changesInstant list of recent changes to "deployit" — the semantic changelog derived from its commits. No AI processing: responds in under a second, costs nothing, and never counts against any quota. Use this FIRST for "what changed", "what's new", "since when" questions; escalate to ask_product_expert only when you need an investigated answer.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | How many days back (default 14, max 90). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does it well: it discloses no AI processing, sub-second response time, zero cost, and no quota consumption. It doesn't detail the exact output structure, but for a simple changelog list the disclosed traits cover the most decision-relevant behavior.
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 three tight sentences, each earning its place: the first defines the resource, the second clarifies performance/cost behavior, and the third gives routing guidance. It is front-loaded with the core purpose and contains no filler.
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 tool with one optional, well-documented parameter and no output schema, the description covers purpose, behavior, and usage boundaries. The return value is inherently implied by 'list of recent changes,' and the sibling relationship is handled explicitly. Nothing essential is missing for safe invocation.
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 only parameter, 'days', is already fully documented in the schema with default and max values. The description adds no additional parameter-specific guidance, so the schema does the heavy lifting and the baseline of 3 applies.
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 specifies exactly what the tool returns — an instant list of recent changes to 'deployit' derived from commits as a semantic changelog. It clearly distinguishes this from the sibling ask_product_expert by framing it as the lightweight, non-AI option for 'what changed' questions.
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?
Usage guidance is explicit and prescriptive: 'Use this FIRST for ... questions' and 'escalate to ask_product_expert only when you need an investigated answer.' This gives the agent a clear decision rule for choosing between the two sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are mostly distinct: server_info is clearly separate, and get_recent_changes is explicitly positioned as the fast first stop for change-related questions while ask_product_expert handles deeper investigation. Some overlap exists around 'recent changes', but the descriptions provide clear routing guidance.
Two tools follow a clear verb_prefix pattern (ask_product_expert, get_recent_changes), but server_info breaks the pattern by being a plain noun phrase. This is a minor deviation rather than a chaotic mix, so the set remains readable and predictable.
Three tools is well-scoped for the stated purpose: deep product Q&A, fast changelog retrieval, and server/index orientation. Each tool earns its place and none are redundant.
The tool surface covers the full knowledge-retrieval flow: orient with server_info, get immediate change summaries with get_recent_changes, and perform deep investigation with ask_product_expert. Answers include sources and verification statuses, so there are no obvious dead ends or missing operations for this domain.