Attester Oracle

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

Beyond the annotations (readOnly, openWorld, idempotent), the description adds substantial behavioral context: the answer is deterministic, sourced from the real published artifact, signed, and includes typosquat-adjacency flags on misses. It also discloses rate limits and shared quota with /demo/v1/* HTTP routes, which is valuable for the agent.

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?

The description is three sentences long with every sentence adding value: purpose, behavioral details, and rate limits. It front-loads the core question and avoids any fluff or repetition of schema fields.

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?

Given the simple parameter set and the existence of an output schema, the description covers purpose, behavior, constraints, and alternative access routes. It is complete for this tool; no critical information 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?

With 0% schema description coverage, the description compensates by explicitly mentioning both parameters: 'PyPI or npm' clarifies the ecosystem enum, and 'package name' explains the name parameter. This gives the agent enough semantic understanding even though the schema omits descriptions.

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 opens with a direct question that precisely defines the tool's capability: determining whether a PyPI or npm package name exists. This is a specific verb+resource (exists + package), clearly distinguishing it from sibling tools like symbol_exists and version_diff.

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 clear context for when to use this tool (package existence checks) and provides usage policy details including free quota limits and a paid HTTP route for higher volume. It does not explicitly name alternatives but the purpose is unambiguous, so no exclusions are needed.

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?

The description discloses rate limits (25 calls/day/IP), reset time (00:00 UTC), and the paid alternative route, adding behavioral context beyond the annotations (read-only, idempotent). It also mentions 'closest-match suggestions on misses,' which clarifies return behavior. Annotations already cover safety, so the description enriches without contradicting.

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?

The description is two concise sentences. The first sentence states the primary purpose and behavior, and the second provides rate-limit and pricing alternatives. There is no wordiness or redundancy—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?

Given the tool's simplicity, an output schema exists, and annotations are present, the description covers the core purpose, behavior on misses, and usage limits. It does not explain the output schema or error cases, but those are covered by structured data. Missing version semantics is a minor gap, but overall the description is contextually sufficient.

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 that ecosystem is PyPI or npm, and symbol refers to a function, class, or constant, covering two key parameters. However, it omits the optional 'version' parameter entirely, leaving its meaning and default to the schema. Partial compensation is provided, but not complete.

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 clearly states the tool's function: checking whether a function, class, or constant exists in a PyPI or npm package. It uses specific verbs ('exist') and resources ('symbol', 'package'), and distinguishes itself from siblings like package_exists or symbol_signature by focusing on existence with closest-match suggestions.

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: you would use this tool when you need to check symbol existence before using it. The description does not explicitly name alternative tools or conditions for when not to use it, but it does provide guidance on free vs. paid routes for high-volume usage, which is a form of usage context.

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 indicate read-only, open-world, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: rate limits (25 calls/day per client IP), sharing of quota with /demo/v1/* routes, reset time, and version-resolution behavior when a version is given. No contradictions with annotations.

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?

The description is compact: two sentences with the core purpose first, then usage limits and paid upgrade path. No redundant filler, and each sentence delivers distinct information (function, quota, alternative).

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 presence of an output schema covers return values, so the description focuses on purpose, quota, and version resolution. However, it omits explanations for the ecosystem/package parameters and doesn't mention any prerequisites or relationship to sibling tools. For a simple lookup tool with good annotations, this is moderately complete but has clear 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 0%, so the description must compensate. It adds meaning for 'version' ('resolved at a pinned version when given') and implies 'symbol' is the target, but it does not clarify the 'ecosystem' enum values or the 'package' parameter. This leaves half the parameters under-explained.

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 clearly states the tool returns 'Exact signature, structured params, docstring summary, and deprecation status for one symbol', which is a specific resource and scope. It distinguishes itself from siblings (package_exists, symbol_exists, version_diff) by describing a detailed signature lookup rather than existence or diff checks.

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 implies usage (resolve a symbol's signature, especially with a pinned version) but does not explicitly compare against sibling tools or state when to prefer this over symbol_exists or version_diff. It provides context about rate limits and paid alternatives, but not tool-selection guidance.

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 indicate readOnly, idempotent, and non-destructive behavior. The description adds valuable operational details: free quota, per-IP rate limiting, shared quota with demo routes, midnight UTC reset, and paid alternatives. This goes beyond the annotations without contradicting them.

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?

The description is concise and well-structured: the first sentence states the core purpose and outputs, the second provides usage constraints and a paid alternative. No unnecessary words, and important information is front-loaded.

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?

Given the presence of an output schema, the description does not need to detail the return format, and it appropriately covers rate limits and paid routes. The description explains the diff and classification outputs, which is sufficient for an agent to decide whether to use the tool. Minor gaps like version format and explicit sibling differentiation prevent a perfect score.

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 input schema has 0% description coverage, so the description must compensate. It mentions 'two pinned versions of one package,' which implies from_version and to_version, but it does not explicitly define each parameter or mention the ecosystem enum. The parameter names are self-explanatory, giving some semantic help, but the description could have added more detail (e.g., version format, accepted ecosystems).

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 clearly states the tool's function: it produces a symbol-level diff between two pinned versions of a package, listing added/removed/changed signatures, new deprecations, and a breaking/additive/neutral classification. This is specific, uses a clear verb and resource, and distinguishes itself from sibling tools that check existence or signatures rather than comparing versions.

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 provides clear context about usage constraints: free with a 25-calls/day limit shared with demo routes and a paid alternative for higher volume. However, it does not explicitly mention when to use this tool versus the sibling tools (e.g., for single-symbol lookups), leaving that to the agent to infer from the purpose.

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