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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered structurally. The description usefully discloses that the response includes full Markdown text (not just metadata), but says nothing about not-found behavior or size of the payload.

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?

A single sentence with no filler, front-loading the resource and the notable payload detail. Nothing is wasted and nothing important is buried.

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?

With an output schema present, the description need not explain return fields, and it correctly flags the Markdown body as part of the result. It is nearly complete, missing only a hint about how names are matched or what happens on an unknown name.

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 there is a single parameter, so the schema already documents that 'name' is the framework name from list_frameworks. The description adds no format or matching semantics beyond that, so the baseline 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?

States a specific verb and resource ('Return one framework's details and its full Markdown text'), clearly a single-item fetch rather than a list. It does not explicitly name list_frameworks as the sibling it contrasts with, so the reader must infer the single-vs-many distinction from the word 'one'.

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 is implied by 'one framework's details', and the schema's name field points at list_frameworks as the way to discover names, but the description itself gives no explicit when-to-use or when-not-to-use guidance. Adequate but minimal.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds nothing beyond annotations or schema - no note on behavior when the id does not exist, no error semantics - so it contributes little behavioral context.

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?

A single well-formed sentence with no filler, and the core action is front-loaded. It is arguably under-specified rather than over-long, but it wastes nothing.

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?

With an output schema present the description need not enumerate return fields, and annotations cover the read-only profile, so the minimal text is passable. However, for a retrieval-by-id tool it omits any handling note for missing/invalid ids, leaving a modest gap.

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% for the single 'id' parameter (minimum 1), so the schema fully documents it. The description adds no format, range, or sourcing detail beyond what the schema provides, which is the expected baseline when the schema does the work.

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 gives a clear verb+resource pair ('Return the full record for one idea'), and the singular 'one idea' implicitly distinguishes it from list_ideas and search_ideas. It does not name any sibling explicitly, so the differentiation is inferential rather than stated.

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?

There is no explicit when-to-use guidance, no mention of prerequisites (e.g., that a valid id must be obtained first), and no routing to alternatives such as search_ideas or list_ideas. Usage must be inferred entirely from the tool name and singular phrasing.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds the categories of computed output, but since an output schema exists, much of that restates structured data rather than adding new behavioral context such as freshness, live-vs-cached computation, or cost.

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?

A single sentence that front-loads the verb and lists the returned aggregates with zero filler. Every clause carries information about what the caller gets.

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 zero-parameter read-only aggregate tool with an output schema defining the return shape, the description covers what is needed to call it correctly. The only omission is guidance on when to choose it over list_ideas/search_ideas, which is a minor gap.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-parameter tool is 4. The schema confirms an empty argument object, so no gap exists.

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 ('Return') and resource, and enumerates exactly what is computed: total ideas, counts by domain, counts by status, and most-used tags. That aggregate nature inherently separates it from siblings like get_idea and list_ideas, but it never names or contrasts those siblings explicitly, so it stops short of a 5.

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 is only implied: an agent can infer this is for summarized/aggregate views rather than enumerating ideas, but the description gives no explicit when-to-use, no statement of when list_ideas or search_ideas is preferable, and no note on whether filters apply.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is settled. The description adds the shape of each returned record but says nothing about pagination, volume limits, or ordering behavior for a list endpoint.

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?

One front-loaded sentence with no filler; the verb and resource lead and the returned fields follow. It is tight, though the return-field enumeration overlaps with what the output schema likely already provides.

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 return values need no elaboration, and the category parameter is documented in the schema. For a simple zero-required-parameter list tool, the description is nearly sufficient; only usage routing to get_framework is missing.

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% ('Only this category.'), so the schema already explains the single optional category filter. The description adds no meaning beyond that, which is the baseline for fully covered schemas.

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 ('List') and resource ('analytical frameworks'), and enumerates what each entry contains, which distinguishes it from the singular get_framework sibling. It does not name the sibling explicitly, but the singular/plural pair makes the split obvious.

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 is only implied: an agent can infer this is the discovery call before get_framework, but the description never says when to use it instead of get_framework or search_ideas. No prerequisites or exclusions are given.

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 readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds the 'newest first' ordering trait, which is useful beyond the annotations, but says nothing about pagination behavior or what the result set looks like.

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?

A single front-loaded sentence with zero waste; verb, ordering, and filter list are all delivered immediately.

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 return values need not be explained, and annotations cover the safety profile. The description covers ordering and filters adequately, leaving only minor gaps around parameter detail and sibling routing.

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 40% (only limit and offset are documented in the schema). The description names the three filter parameters (domain, tag, status) but adds no matching semantics, format, or value meaning beyond the bare names already visible in the schema.

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 ('List') and resource ('ideas') and adds ordering ('newest first') plus the filterable dimensions. However, it does not distinguish this from the sibling search_ideas, which an agent could reasonably confuse with filtered listing.

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?

'Optionally filtered by domain, tag, or status' implies when the tool is useful, but there is no explicit when-to-use vs. search_ideas guidance, nor any exclusion conditions. Usage is left partially 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 only cover readOnlyHint and openWorldHint. The description adds rich behavioral detail beyond that: ranking order (best match first), snippet format with [brackets], and the AND-to-OR fallback behavior with a `matched` field indicating the rule applied. This fallback behavior is unusual and valuable to disclose.

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?

Three sentences, no filler. Front-loads the search scope, then ranking and snippet, then the fallback rule. Every sentence earns its place.

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 return values need not be explained, and the description still usefully covers ranking, snippet format, and fallback semantics. Only the lack of explicit alternative-tool routing keeps it from being fully complete.

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 parameters are fully documented in the schema. The description does not add syntax or format details for query/limit/domain, so baseline 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?

States a specific verb (full-text search) and enumerates the exact fields searched (titles, domains, problems, insights, assumptions, tags). This clearly distinguishes it from list_ideas and get_idea among siblings.

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 is implied by 'full-text search' versus the list/get siblings, but there is no explicit when-to-use or when-not-to-use guidance, no mention of when to prefer list_ideas or idea_stats instead.

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 declare readOnlyHint=false, destructiveHint=false, and openWorldHint=false, so the agent knows this is a non-destructive write operation. The description adds that it returns the id and stored record. However, it doesn't mention permission requirements, rate limits, or what happens on duplicate titles. With annotations covering safety, this is adequate but not rich.

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?

Two concise sentences that front-load the core action and then note the return value. No wasted words, though the second sentence is somewhat redundant given the output schema.

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?

The tool has 7 parameters, an output schema, and annotations, so the description doesn't need to explain return values in detail. However, it lacks usage guidance and behavioral nuances like validation rules or error handling. It is minimally complete but leaves gaps.

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%, so all parameters are fully documented in the schema. The description adds no extra parameter semantics beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Save a new idea to the knowledge base.' An agent can distinguish this from siblings like get_idea or update_idea, though it doesn't explicitly contrast with them. The purpose is clear but lacks sibling differentiation.

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 offers no guidance on when to use this tool versus alternatives such as update_idea (for existing ideas) or search_ideas. There is no mention of prerequisites or context. This is a significant gap for a creation tool with multiple related siblings.

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 readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavior beyond that: partial-update semantics ('Omitted fields stay as they are') clarify that unspecified fields are preserved rather than nulled. It says nothing about required permissions, irreversibility, or the special clearing behavior the schema mentions for some fields.

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?

Three short sentences, front-loaded with the core action and the partial-update rule. Slightly clipped by the trailing 'Returns the updated record', which restates information already available in the output schema.

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?

The output schema exists, so the description is not obligated to explain return values, and the patch semantics are covered. But for an 8-parameter mutation tool at 38% schema coverage, the definition omits field-level guidance and the note that some fields (e.g. tags) are replaced wholesale rather than merged, leaving real gaps.

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 only 38% for 8 parameters, so the description carries the burden of compensating and does not: it never enumerates the updatable fields (title, domain, status, insight, problem, assumptions), so field-level meaning is missing. The only useful addition is the generic 'omitted fields stay' rule, which does not resolve which fields can be set or how to clear them.

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 and resource ('Change one or more fields of an existing idea'), which an agent can immediately distinguish from the read siblings (get_idea, list_ideas) and the create sibling (store_idea). It does not name those siblings explicitly, so it stops short of full differentiation.

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 wording implies the appropriate context (modifying an already-existing idea), and the PATCH-style contract signals that this is the tool for partial edits rather than recreate-and-replace. However, it never names an alternative or states an exclusion, so the routing guidance is only implied.

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