Storra for Creators

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 useful payload context — that the full story, its direction, the support offered, and charity details come back — which matters since there is no output schema. It says nothing about lookup failure behavior or whether the slug is case-sensitive.

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 sentence, front-loaded with the verb and the singular scope, then the payload enumerated compactly. Nothing is redundant or padded.

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 single-parameter read tool with full annotation coverage and no output schema, the description's summary of returned content is the right addition. Minor gaps remain around failure modes and slug format, but nothing needed to call it correctly 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?

There is a single parameter and schema coverage is 100%, so the schema already documents the slug fully, including its origin in a search result. The description adds no format, casing, or error semantics beyond that, so 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?

States a specific verb (get) and resource (one story), and the phrase 'one story in full' contrasts implicitly with the sibling search_stories_to_tell, which returns many. It does not name the siblings, so differentiation is inferable rather than explicit.

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?

No when-to-use or when-not-to-use guidance is given, and no alternative is named. The only hint about invocation context is in the schema ('from a search result'), which is not part of the description.

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, idempotentHint, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds that each entry includes a story count, which is genuinely useful return-shape context absent from any output schema, but it says nothing about ordering, empty results, or scope limits.

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 short sentences, zero filler, and the primary function is stated first with the downstream use-case second. Every clause 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?

For a zero-parameter enumeration tool with no output schema, the description covers both what is listed and what each entry contains (a story count). Adding the nominal follow-up tool name would make it fully self-sufficient, but nothing essential to invoking it correctly 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?

The tool takes zero parameters, so the baseline of 4 applies — there is nothing for the description to disambiguate. The sentence does confirm the listing is unfiltered, which is consistent with the empty 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?

The description gives a specific verb (List) and resource (causes stories are filed under) and even states the return content (story count per cause), so the agent knows exactly what it produces. It doesn't explicitly contrast itself with get_story or search_stories_to_tell, but the resource is distinct enough that confusion is unlikely.

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?

"Use a cause as the filter in a search" tells the agent why the result matters — to obtain a valid filter value for a search — which is useful implied routing. However, it never explicitly names search_stories_to_tell as the follow-up tool or states when this listing should be preferred over other lookups, leaving the agent to infer the workflow.

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 readOnly, idempotent, non-destructive, closed-world behavior. The description adds real behavioral value by disclosing which fields the query is matched against (titles, summaries, charities, causes, places) and that results include a link to each story page, so the agent knows the shape of the match logic and output.

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: purpose first, matching/return behavior second. No filler, no redundancy, front-loaded with the core action.

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?

No output schema, but the description covers what comes back (best matches with a link to each story page) and the schema fully documents all five filter parameters. It could say more about ranking or result limits, but for a search tool it is nearly 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 each parameter is already documented (cause deferring to list_causes, limit default/max, query examples). The description's statement that matching spans titles/summaries/charities/causes/places lightly enriches the query parameter, but adds little beyond the schema baseline.

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?

Clear specific verb+resource: search real charity stories, with the creator-facing use case stated. It implicitly distinguishes itself from get_story (singular retrieval) by being a search over multiple fields, though it never names the sibling tools explicitly.

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 gives context (stories a creator could make a video or post about) but no explicit when-to-use vs when-not, nor routing to get_story or list_causes beyond the inline 'Use list_causes for the values' note on the cause parameter. Usage is implied rather than prescribed.

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