Agentify — search engine for AI agents

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

readOnlyHint=true already tells the agent this is a safe read, and the description corroborates it by framing the call as a retrieval. The parenthetical '(all products, current)' usefully signals return scope (no historical entries), but nothing is said about behavior for unknown domains, empty results, or result size.

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 action and resource, with the input requirement and example trailing. Every clause carries information and nothing is 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 one-parameter read tool with no output schema, the description covers what is fetched and how it is identified. Return shape and error behavior for an unknown domain remain unspecified, which is the only 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?

With 0% schema description coverage, the description must carry the parameter alone, and it does: the single 'domain' argument is defined as the company's domain with a concrete example ('example.com'). That removes the main ambiguity (bare name vs. URL vs. full domain) without spelling out accepted formats like scheme prefixes.

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 ('Get') plus a specific resource ('a company's complete AgentDNA catalog') and an explicit scoping qualifier ('all products, current') keyed by domain. It does not differentiate itself from siblings like agentify_search or agentify_get, so an agent cannot tell from the description alone when this beats searching.

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: fetch the full catalog for a known company domain, with 'example.com' as an example input. There are no explicit exclusions and no mention of the sibling tools (agentify_get, agentify_search, agentify_stats) that might be the better choice for partial 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?

readOnlyHint=true already tells the agent this is a safe, non-mutating read, so the description's burden is lighter. "Full record" usefully signals completeness relative to search results, but nothing is said about behavior when an id is unknown or stale, nor about permissions or rate 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?

A single sentence with the verb, scope, key parameter and provenance all front-loaded; there is no filler or redundant restatement of the tool name.

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 tool with readOnlyHint already declared and no output schema, this covers what an agent needs to invoke it correctly. The only material omission is the failure mode for an invalid or missing id, which matters slightly for a lookup tool.

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%, so the description must carry parameter meaning — and it does, explaining that id identifies a single result and originates from agentify_search, which is the most important semantic for this parameter. It does not specify the id format (opaque string vs UUID) or whether it must be exact, keeping it just short of full compensation.

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 ("Get the full record") plus a specific resource ("one Agentify result") scoped by id. The parenthetical naming agentify_search as the id source implicitly contrasts this single-record fetch with the sibling's search behavior, so the agent can tell them apart without opening a schema.

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 "(from agentify_search)" establishes the natural workflow — search first, then fetch by id — so usage is implied rather than stated. There is no explicit when-not guidance (e.g., that this should not be used to enumerate results, or that agentify_stats covers aggregate counts).

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 the safety profile (readOnlyHint=true, openWorldHint=false), and the description adds genuinely non-structured context: results are seller-maintained via AgentDNA, ownership is verified, and machine results carry a live-handshake witness from AETHER. It stops short of describing result shape, ranking, or pagination behavior, which matters given 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?

Three compact sentences, front-loaded with the identity of the resource and then the result domains. The parentheticals are dense but every clause carries information an agent would otherwise have to guess.

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 9-parameter, no-output-schema tool, the description does the important work: it says what kinds of objects come back and what qualifies them. The missing pieces — how results are ordered, what a page looks like, and whether type=all merges domains — are secondary but not trivial.

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% across 9 parameters, so the description must compensate. It does map meaning onto several filters — price/availability imply max_price and in_stock, verified ownership implies verified_only, and the three named entity kinds correspond to the type enum — but domain, currency, limit, and offset get no semantic treatment anywhere.

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+resource: "Search Agentify, the search engine for AI agents," followed by an explicit enumeration of the three result domains (products, companies, machines). An agent can tell this is a broad, multi-entity search rather than a fetch-by-id or a stats call, though no sibling tool is named to sharpen that 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?

"Use it instead of crawling websites" gives a clear when-to-use rule plus a named alternative behavior to avoid. It does not, however, say when to prefer agentify_get, agentdna_catalog, or agentify_stats over this broad search, so routing vs. siblings is left implicit.

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?

readOnlyHint=true already covers the safety profile, so the description's only added value is that the response concerns index size and freshness. It does not say whether size means record count or bytes, or whether freshness is a timestamp or an age, and with no output schema the description is the sole source for that. Too thin for a zero-param read tool whose whole point is its return content.

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?

It is certainly concise and the key concept is front-loaded, but it is under-specified rather than efficient: a single four-word fragment with no sentence structure or actionable claim. Brevity here costs clarity instead of buying it.

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 zero-param read this should be easy to complete, yet the agent still cannot tell what the response contains (counts, byte size, last-indexed timestamp) or how to use it relative to the sibling search/get tools. Annotations cover safety and there is no output schema, so the description needed to carry the return-value meaning and does not.

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 no parameters, so there is no parameter semantics to explain; the baseline applies. Nothing in the description misleads about inputs.

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 phrase "Size and freshness of the Agentify index" tells the agent what data the tool surfaces, which distinguishes it from siblings like agentify_get and agentify_search. But it is a noun fragment with no verb, so it never states that the tool reports/returns these metrics. The purpose is inferable rather than clearly asserted.

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 statement of when to call this versus the three sibling tools (agentdna_catalog, agentify_get, agentify_search), nor any prerequisite or exclusion. The agent must guess that this is a metadata/introspection call to make before searching.

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