profile

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

No annotations are provided, so the description carries the full burden. It does disclose one genuine behavioral trait beyond structured data: the contact boundary where no raw email is published, which tells the agent what it will not receive. However, it says nothing about whether this is a read-only operation, freshness of the availability data, or any permission requirements.

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 no filler; each of the three listed content types earns its place. It is slightly terse for a tool whose subject (whose availability) is ambiguous.

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, no annotations, and no parameters, the description is the only source of information. It covers the returned fields and the email-privacy constraint, but leaves the data source, scope, and freshness unstated for a tool whose subject is not identified.

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. The description correctly adds no parameter detail because there is nothing to parameterize.

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 names the returned content (availability, work scope, contact boundary) but uses a noun phrase rather than a verb+resource statement, and it never says whose availability is fetched. It is distinguishable from get_project or search_faq, but it overlaps noticeably with the sibling get_profile_summary without clarifying the difference.

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 when-to-use guidance and no reference to any alternative, despite get_profile_summary being an obvious candidate for the same profile-adjacent information. The agent must infer the choice from the tool name alone.

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?

No annotations are provided, so the description carries the full behavioral burden. It states the content bucket but not whether the response is cached, what happens for unknown entities, or any auth/rate considerations. For a zero-parameter lookup with no annotations this is thin.

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 with the content list front-loaded after the label. Efficient, though the colon-list style is dense and slightly telegraphic.

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 must describe the return surface — and it does list the main fields. But with no annotations and no input parameters, the omission of return format, resolution failures, and sibling boundaries leaves 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?

Zero parameters, so there are no parameter semantics to convey; baseline is 4. The description does clarify what the returned entity fields are, which is a small bonus.

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 resource (profile summary) and enumerates its contents (entity name/aliases/@id/sameAs, availability, pointers), which distinguishes it from sibling get_availability and get_project. However, it never explicitly contrasts with those siblings, so an agent must infer 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?

No when-to-use guidance, no alternatives named, no exclusions. Nothing tells the agent when to pick this over get_availability or get_project despite those siblings plausibly covering overlapping data.

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?

With no annotations, the description carries the full burden. It helpfully enumerates the returned fields (ownership, builtBy, canonical URL, links, proof count), but says nothing about what happens with an unknown slug, auth requirements, or whether the 'indexed' snapshot can be stale.

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 no filler; the identifier and the return contents are both stated 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?

For a one-param lookup with no output schema, the description does the necessary work by listing the fields returned. Only minor gaps remain around error behavior and slug format.

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?

One required param at 0% schema coverage, so the description must compensate. 'By slug' establishes that the param is the project's slug identifier, but adds no format or normalization guidance (URL form, casing) beyond that single inference.

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 ('get ... one project by slug') and enumerates the payload, which implicitly separates it from list_projects and get_proof. It never names a sibling explicitly, so the differentiation is inferred 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?

The phrase 'by slug' implies the usage context: fetch a single project when you already have its slug. There is no explicit when-to-use/when-not guidance and no pointer to list_projects for browsing or search_faq for other lookups.

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?

With no annotations, the description carries the full burden. It does disclose one real behavioral trait beyond the schema: unknown slugs return an error. It says nothing about read-only nature, auth/permission requirements, or rate limits, which for a proof/verification lookup are plausible concerns.

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 compact sentences, front-loaded with the resource and the mode switch. Nothing is padded, though the second sentence is a terse error note rather than substantive detail.

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, no-output-schema lookup this is nearly adequate: both modes and the error case are covered. It still leaves "claim gates" undefined and does not clarify what shape the proof data takes, which is the main thing an agent needs to use the result.

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% for the single slug parameter, so the description must compensate. It does explain the semantic effect of supplying slug (switches to per-project proof links), but gives no format, naming, or lookup rules for valid slugs.

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?

"Verification proof" names the resource and the two output modes (claim gates vs per-project proof links), but the verb is implied rather than stated and "claim gates" is unexplained jargon. An agent gets the gist but cannot confidently distinguish this from get_project or get_profile_summary without guessing.

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 the usage rule — pass a slug for per-project proof links, omit it for claim gates — which is genuine conditional guidance. However, it names no alternatives and does not say when this tool should be preferred over its 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?

With no annotations, the description carries the full burden and does well: it discloses that unknown filter values return an empty list rather than an error, that matching is case-insensitive, what fields each entry carries (ownership, builtBy), and warns against miscounting the nested Frontend Mentor Lab entry. Missing auth/permission or pagination context, but for a fixed 17-entry read list this is solid.

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?

Four front-loaded sentences with the scope stated first and the counting caveat placed where it prevents misuse. Dense but each sentence carries real information; nothing is redundant.

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, and the description partially compensates by naming returned fields (ownership, builtBy) and the entry count. The only real gap is the unexplained lens enum, which is mitigated by self-descriptive values like 'ai' and 'web3'.

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 the tag parameter well (Title Case display strings, case-insensitive matching across 'web3'/'Web3'), but the lens parameter and its five enum values are never mentioned, leaving one of two parameters undocumented.

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 with scope: 'List the canonical portfolio case studies (17 entries)'. It is clearly distinct from the singular get_project sibling by being a collection lister, though it never names that sibling 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?

Implies usage via the filter semantics ('Optional filters combine with AND') but gives no explicit when-to-use guidance or routing against alternatives like get_project or search_faq. An agent must infer the choice.

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?

With no annotations, the description carries the full burden. It usefully discloses case-insensitivity and result ordering, which an agent cannot get from the schema, but says nothing about pagination, the meaning of limit, result shape, or any auth requirements.

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, front-loaded with the core capability and followed by a concrete example that earns its place by clarifying ranking semantics. 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?

No output schema and no annotations, so the description should carry more. It covers search semantics well but omits the return format, how limit affects results, and whether results are paginated or ranked with scores.

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% for both parameters, so the description must compensate. The example 'who is mark siazon' illustrates the query parameter's intent, but limit (max 20, min 1) is never explained or mentioned, leaving half the parameters undocumented in both places.

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 names a specific verb and resource (FAQ search) plus a matching behavior, so an agent immediately knows what it does. Sibling tools are all get_*/list_* domain lookups with no FAQ overlap, so no explicit differentiation is needed, but the description also never routes against 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?

It describes how matching works (case-insensitive, exact matches rank first) but gives no when-to-use or when-not-to-use guidance and names no alternative tool. The ranking note implies a use case (looking up a specific question) but the agent must infer it.

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