Space Kitty Archive

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

Goes well beyond the annotations by disclosing that invocation is billed ($0.20 USDC on Base Sepolia testnet via x402), which is critical behavior an agent cannot get from readOnlyHint/idempotentHint. It also enumerates the payload contents. It stops short of saying what happens on payment failure or whether a failed call is charged.

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 paid framing and delivers the content list in one dense sentence with no filler. Minor redundancy: payment is mentioned twice (

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 no output schema, the description does a fair job of describing the return payload, but it leaves the single required input undefined and says nothing about the relationship to the six sibling tools. For a paid, irreversible-cost call, that is a meaningful omission.

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, yet it never explains what 'slug' identifies (topic, paper, or dossier identifier) or what the markdown vs json 'format' choice controls. The only parameter hint is the implicit idea of a 'dossier', which is not enough for a two-parameter tool with an undocumented enum.

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+resource ('Full research dossier') and enumerates the bundled artifacts (synthesis, claims, benchmarks, timeline, glossary, bibliography), which makes the scope concrete. It differentiates implicitly via 'Full' against the sibling preview_dossier, but never names it, so an agent must infer the contrast.

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: the 'PAID per call' framing signals cost awareness and 'Full' hints at the cheaper preview, but there is no explicit when-to-use guidance, no mention of preview_dossier or get_research_pack as alternatives, and no prerequisites such as needing a valid slug from list_topics.

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 profile is covered. The description adds genuinely non-derivable context: the accepted id prefixes with concrete formats, the license-dependent abstract inclusion, and a 'Free' cost signal. It stops short of describing error behavior for invalid ids.

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 dense sentence with the retrieval scope front-loaded, followed by the id formats and the two material caveats (license-gated abstract, free). No filler or repetition of annotation data.

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 read with no output schema, the description covers the essentials: what is returned (full metadata plus abstract when licensed), how to address the record, and that it costs nothing. A brief note on the response envelope or invalid-id behavior would close the remaining 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 0% — the single 'id' property is a bare string with no description — so the description must carry the burden, and it does: it documents five prefix formats (arxiv:, doi:, pmc:, nct:, openalex:) that the schema alone would never convey. Minor gap: no note on whether the prefix is optional or required.

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+resource ('Full metadata for one record by archive id') and enumerates the accepted id namespaces, making it obvious this is a single-record lookup rather than a search. It doesn't name a sibling such as search_archive or get_dossier to sharpen the boundary, 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: if you hold an archive id, call this. There is no explicit when-to-use/when-not, no mention of when to prefer search_archive to first obtain an id, and no statement about what happens with an unknown or malformed id.

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 safety (readOnly, idempotent, non-destructive), so the description's real contribution is commercial behavior: per-call payment via x402, exact price, and settlement chain (USDC on Base Sepolia testnet). That is genuinely useful context an agent cannot get from annotations. It stops short of saying what happens on payment failure or whether repeated calls are billed again despite idempotency.

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?

Payment mode is front-loaded before payload and price, which is the right order for a paid tool. Minor waste: 'x402' appears twice and the closing parenthetical ('USDC on Base Sepolia (testnet), x402') is awkwardly nested.

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 read-only single-parameter composite fetch with no output schema, the description fully enumerates what comes back and discloses the payment prerequisite. Missing only edge-case behavior (payment failure, unknown topic, billing on retry), which is a modest gap rather than a blocking one.

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?

Only one parameter ('topic'), and the schema already documents it at 100% coverage, so the baseline is 4. The description adds nothing about slug format or lookup failure behavior, but nothing is required either.

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+resource ('Topic research pack') and enumerates the exact payload: topic dossier, 50 most influential papers, 25 newest papers with licensed abstracts, and related clinical trials. That itemization implicitly distinguishes it from get_dossier and get_paper, but no sibling is named 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 'PAID per call' framing plus the $0.20 price gives an agent a cost-based reason to hesitate, and the contents imply this is the bundle option versus preview_dossier/get_dossier. However, it never says when to prefer this over the cheaper siblings or whether a preview/dossier lookup should come first.

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, destructiveHint=false and openWorldHint=false, so safety is fully covered. The description adds genuine value by disclosing the exact content of the response and its free pricing. It omits any limits (how many papers are returned, truncation) which would matter for a preview-style tool.

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 fragment sentence that front-loads the resource and enumerates returned fields with no filler. The clipped 'Free.' is terse but does carry pricing information, so nothing is wasteful, though the telegraphic phrasing borders on under-specification.

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 exists, so the description reasonably lists returned components, and annotations cover safety. But for a single-required-parameter tool, the unexplained slug and the lack of any guidance on obtaining it or on result size leave a meaningful 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?

There is one required parameter, slug, with 0% schema description coverage, so the description must compensate and does not. It never says what a slug is, where it comes from (presumably list_topics), or its format, leaving the only required input unexplained.

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?

Names a specific resource (topic overview) and enumerates the payload: description, key concepts, dossier preview, influential and newest papers. It is clear what the tool returns, but it never distinguishes itself from the sibling get_dossier or preview_dossier, which overlap heavily with 'dossier preview'.

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 trailing 'Free.' implies a cost tradeoff versus paid siblings like get_dossier or get_research_pack, which is an implicit usage signal. However, there is no explicit statement of when to call this instead of preview_dossier or get_dossier, so the agent must infer.

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, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely new behavioral context: the listing surfaces per-topic paper counts and whether a premium dossier exists, and that the call is free — useful for deciding whether to escalate to a paid dossier tool.

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 zero filler; the resource, the optional filter, the returned fields and the cost signal all appear up front. Nothing to trim.

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, but the description names the key return fields (topics, paper counts, dossier availability), which is what an agent needs to decide whether to follow up with get_topic or get_dossier. Minor gaps: no ordering, pagination or result-size expectations for a list endpoint.

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 one optional parameter at 100% schema description coverage, the schema already explains the domain slug with concrete examples. The description only restates that the domain scopes the listing, adding no format or matching semantics beyond 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 and resource ("List the archive topics") and previews the payload: paper counts and a premium-dossier flag. It implicitly contrasts with the singular get_topic and with dossier tools, but never names a sibling to sharpen the boundary.

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 for one domain" tells the agent the filter is optional, and "Free" hints at a cost/tier distinction versus premium siblings like get_dossier or preview_dossier. However, there is no explicit when-to-use-this-instead-of-get_topic or search_archive guidance, so the routing is left 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 profile is covered. The description adds genuinely useful behavioral detail that annotations cannot: exactly what comes back (summary, table of contents, statistics, verification record, two sample claims), which matters because there is no output schema. It omits failure behavior for an unknown slug, keeping it below 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?

One compact sentence, front-loaded with the tool's role and then the payload contents. No filler or redundancy.

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 simple one-parameter read tool with no output schema, the description does the important work of enumerating the returned sections. It falls short only on input semantics for 'slug', which is the one thing an agent still needs in order to call it successfully.

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 0% for the single required parameter, so the description carries the full burden of explaining it — yet the word 'slug' never appears and nothing says what identifies a dossier or where to obtain one (e.g., from search_archive or list_topics). An agent must guess the expected identifier 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?

Specific verb ('preview') plus resource ('dossier'), enriched by an enumeration of what the preview contains (summary, TOC, statistics, verification record, two sample claims). The word 'premium' implies a fuller sibling (get_dossier) exists, but it is never named explicitly, 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?

'Free preview' implicitly signals when to use it — when the agent wants sample content without committing to the full dossier — but there is no explicit statement of when-not to use it or a named alternative among the siblings (get_dossier, get_research_pack). Usage must be inferred from the adjective 'preview'.

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, non-destructive and openWorldHint=false, so the safety profile is covered. The description adds real context beyond that: the scope of the indexed corpus, the shape of results (ranked, with highlighted snippets, identifiers and links), and that it is free of charge — valuable since there is no output schema.

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: what it searches first, what it returns second. Every clause carries information (corpus scope, ranking, snippet/highlight output, cost) with no 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?

With six parameters at low schema coverage and no output schema, the description should clarify the type/kind filters and any empty-result or paging behavior; it covers only corpus scope and return shape. Adequate to call the tool correctly on the required `query`, but incomplete for the optional filters.

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 only 33%, so the description must compensate and it does not — kind, type, limit, topic and year_from are never mentioned. Critically, it leaves unexplained the overlap between the `type` enum (all/papers/dossiers) and the `kind` enum (preprint/article/review/trial), which is the most likely source of mis-invocation.

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?

Names a specific verb and resource ('Full-text search over indexed frontier research papers, clinical trials and research dossiers') and even enumerates subject domains, so an agent knows exactly what it retrieves. It does not explicitly contrast itself with get_paper/get_dossier, though the mention of 'identifiers and links' implies the retrieval-then-fetch pattern.

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: the mention of returned 'identifiers and links' suggests this is the discovery step before the get_* siblings, but no alternative is named and no when-not condition is given. The 'Free' note is a mild cost hint, not a usage rule.

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