MapleStats MCP

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

Annotations already declare readOnly=true, idempotent=true, destructive=false, openWorld=true, but the description adds real context beyond them: the provenance block in results (source, URL, query time, freshness), the error taxonomy (unknown tool vs. field-level validation error vs. upstream outage), the meta-tool nesting restriction, and the timeout governed by MAPLE_TOOL_TIMEOUT_SECONDS (default 120). A clearer statement of what happens to partially-succeeded calls or whether the timeout aborts mid-flight would push this to 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core action, then organizes the rest under a clear 'Use for:' framing followed by returns and errors. It is slightly longer than needed — the meta-tool exclusion and the error enumerations each run a bit long — but every sentence carries actionable content and nothing is 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 two-parameter dispatcher with no output schema, the description covers the full picture an agent needs: how to obtain valid input, what comes back (typed result plus provenance), how failures surface, the nesting restriction, and the timeout boundary. Nothing material is left unspecified.

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%, so baseline is 3, but the description adds operational meaning the schema cannot: the name value must be an exact string previously surfaced by search_tools/plan_query, and the arguments object is defined by the target tool's own schema rather than this one. The failure mode for a misspelled name is documented, which is genuinely useful for an argument whose valid domain is unbounded.

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 first sentence states a specific verb (run) and resource (one data tool obtained via search_tools or plan_query), immediately distinguishing it from both siblings. It also explicitly scopes what it cannot do (cannot invoke search_tools, call_tool, or plan_query), so an agent can route correctly without opening any schema.

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?

Explicit 'Use for:' guidance pairs with concrete preconditions ('by exact name with arguments that match the inputSchema search_tools returned'). Exclusions are named and the recovery path for the wrong-name case is spelled out ('search again for the exact name'), leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety bar is low. The description still adds real behavioural detail beyond them: it is offline, calls no external API, matches against this server's source map, and returns an ordering of tools plus caveats.

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?

Core purpose and the use/use-instead guidance are front-loaded in the first two paragraphs; nothing essential is buried. The bilingual keyword lists at the end are retrieval scaffolding rather than prose and pad the definition somewhat.

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?

An output schema exists, so the return values need not be fully documented, and the description still summarises what comes back (topics, ordered tools, local portals, caveats). Combined with rich annotations, an agent has everything needed to call it correctly; only the trailing keyword blocks are surplus.

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 0%, so the description must compensate. It explains lang fully (fr localises labels, purposes, caveats and guidance while tool and argument names stay unchanged), and 'question' is self-evident from the example given. The lang explanation is the meaningful addition.

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?

States a specific verb (plan) and resource (which sources answer a question), and scopes it as cross-agency/cross-source. It distinguishes itself from both siblings by contrast: call_tool runs the plan's steps and search_tools finds a single tool.

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?

Explicitly says when to use it ('the first call on a substantive question', with a concrete example) and when not to ('Use search_tools instead to find a single tool for a narrow, single-source need'). It also hands off downstream behaviour to call_tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations cover the safety profile (readOnly/openWorld=false/idempotent), and the description adds genuinely new behavior: it searches only this server's catalogue, calls no external API, returns ranked best-matching tool definitions in list_tools format, and defines the empty-result case with recovery advice. These are traits the annotations cannot convey.

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?

Purpose is front-loaded in the first sentence, followed by use-for, boundaries, alternatives, and an edge-case recovery line. Every sentence carries distinct operational information with no filler or repetition.

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 one-parameter search tool with an output schema and full annotation coverage, nothing an agent needs is missing: trigger, scope, return shape, ranking behavior, language support, and failure recovery are all stated.

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 coverage is 100% and the single query parameter is already well documented, so the baseline is 3. The description adds meaningful strategy beyond the schema: queries work in English or French, and topic words beat tool names, which shapes how an agent should phrase the argument.

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?

States a specific verb (find/search) and resource (data tool) plus the scoping constraint that it searches this server's catalogue only. It explicitly names what it is not (plan_query, call_tool), so an agent can distinguish it from siblings without opening any schema.

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?

Gives an explicit 'Use for' trigger, then hands off with conditions: 'use plan_query instead when a question may span several sources or you do not know where to start' and 'use call_tool to run a tool once you have its name.' That is the full when/when-not/alternative set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.