Fetch one canonical SVV context document from the public facade. Use after search() when you need the actual text.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It conveys that the tool is a read-only fetch from a 'public facade,' implying no authentication or side effects, and states that it returns 'the actual text.' It does not mention error handling or edge cases, but for a simple fetch operation, the key behavioral aspects (safe, public, read-only, returns content) are covered, which is solid though not exhaustive.
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 short sentences, front-loaded with the primary action and resource, followed by usage guidance. Every word earns its place — no fluff, no redundant details, and the structure logically leads from purpose to usage.
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?
Given the simple nature of the tool (one parameter, output schema exists), the description is quite complete: it states what it does, when to use it, and what it returns ('actual text'). The main gap is the implicit derivation of the 'id' parameter, but the reference to search() and the availability of output schema mitigate this. Overall, it provides enough context for correct invocation in most cases.
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?
The input schema has one required 'id' string with zero description coverage. The description does not explicitly explain what 'id' means or how to obtain it, but the guidance 'Use after search()' implies that the id comes from search results, providing indirect semantic context. This partially compensates for the lack of schema description but does not fully clarify the parameter's role or format.
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 clearly states the tool's function with a specific verb ('Fetch') and resource ('one canonical SVV context document') from the public facade. It also differentiates itself from the sibling tool 'search' by framing itself as the next step to obtain the actual text, making its purpose distinct and unambiguous.
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?
The description explicitly states when to use the tool: 'Use after search() when you need the actual text.' This gives direct placement in a workflow and implies that 'search' is the alternative for finding/listing documents rather than fetching content, effectively distinguishing the tool's role.
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.
Some tools overlap in purpose: latest_memory_snapshot, ops_status_summary, and startup_operator_snapshot all provide some form of current state, and agent_query overlaps with search for information retrieval. However, the descriptions clarify distinct intents (e.g., bounded vs. full document search, operational vs. canonical snapshot), so boundaries are mostly clear.
All tool names use lowercase snake_case, but they do not follow a consistent verb_noun pattern. Some names are single verbs (fetch, search) while others are noun compounds (latest_memory_snapshot, ops_status_summary). This mixed style is readable but not predictable.
With 7 tools, the set is well-scoped for a public-facing query and status facade. Each tool serves a distinct role (query, search, fetch, snapshots, status, self-check), and the count feels appropriate without excess or deficiency.
The tool set covers the core needs of a read-only public facade: asking questions, searching documents, fetching content, and retrieving status/snapshots. There is some redundancy among snapshot tools, but no major missing operation for the stated purpose.
