Charitology public research

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 profile is covered. The description adds genuinely useful context beyond that: the counts are catalog-scoped and are not a measure of complete coverage, a caveat that prevents misreading results. It stops short of describing response shape or size, but with the strong annotation set this is a solid contribution.

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 sentences, no filler. The resource list comes first and the interpretive caveat follows, which is the right ordering for an agent skimming for fitness.

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?

There is no output schema, so the description must carry the return-value burden, and it does list the four kinds of content returned (counts, descriptions, export dates, licensing limitations). For a zero-parameter read tool with rich annotations, that is close to sufficient, though response size or pagination behavior is unmentioned.

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 no parameter semantics for the description to explain; baseline of 4 applies. Nothing in the description misrepresents the no-argument nature of the call.

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?

A specific verb ("Read") plus a concrete resource inventory: dataset counts, descriptions, export dates, and licensing limitations. It is implicitly distinguishable from read_public_record and search_public_research (catalog metadata vs. records vs. research), but it never names or contrasts with those siblings, so the differentiation is left to inference.

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 the caveat that counts describe the published catalog rather than complete charity or intervention coverage, which tells the agent how to interpret results. However, there is no explicit when-to-use guidance and no routing statement toward read_public_record or search_public_research.

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 cover read-only, idempotent, non-destructive and closed-world behavior, so the description correctly focuses on what annotations cannot express: that it returns original public fields plus source rights, and that it never fetches the supplied identifier as a URL. That last clause is a genuinely useful disclosure of a non-obvious safety 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?

Two tight sentences; the accepted identifier forms come first and the return/safety clause follows. Every clause carries information an agent would not otherwise have, and nothing is repeated from the schema or annotations.

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 read tool with no output schema, the description covers what is returned (public fields and source rights) and the key behavioral caveat. Gaps remain around how 'dataset' scopes the lookup and what happens when an id does not resolve, but the essentials for correct invocation are present.

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?

With 0% schema description coverage the description must carry the load, and it does add real meaning for 'id' (record id, or an exact source URL for bibliography records). The 'dataset' parameter's four enum values are never explained, so half of the parameters remain semantically underspecified.

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 ('Read an exact published record') and clarifies the two accepted key forms: a returned id or an exact source URL for bibliography records. This implicitly contrasts with lookup-by-query siblings, but it never names read_public_coverage or search_public_research, so differentiation relies on inference.

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 word 'exact' and 'by its returned id' imply this tool is for direct retrieval after a search, not for discovery. However, there is no explicit when-to-use/when-not guidance and no pointer to the search sibling for query-based lookups, leaving the routing decision implied.

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 establish readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false. The description adds useful domain semantics beyond that: it preserves draft review states, source references, and source-specific licensing, and it warns that depth classifications are hypotheses rather than ratings.

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 with zero filler. The core purpose is front-loaded, followed by preservation behavior and a caveat about depth classifications.

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?

There is no output schema, and the description does provide useful return-content context around preserved states, references, licensing, and classification caveats. Still, for a four-parameter search tool with 0% schema description coverage, it leaves query, limit, offset, and enum semantics underexplained.

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 carries the full burden for four parameters. It hints that a single dataset must be selected, but it does not explain query, limit, or offset behavior, nor does it clarify the enum dataset values.

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: "Search one published Charitology dataset." This is clearer than a tautology and distinguishes search from the sibling read tools by verb, though it does not explicitly name those siblings as alternatives.

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 phrase "Search one published Charitology dataset" implies the use case and the required dataset selection. However, it gives no explicit when-to-use or when-not-to-use guidance relative to read_public_record or read_public_coverage.

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