Agenlify AI Agent Directory

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety/isolation profile is covered. The description adds genuine scope information by enumerating what the record contains (setup steps, limitations, human review requirements, pricing review dates, official sources, case studies). It says nothing about behavior on an unknown slug, which is the one remaining gap.

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 and resource front-loaded, followed by the field enumeration. The trailing list is long but each item is a distinct part of the returned record, so it earns its space; nothing is padded or restated.

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 usefully takes on the burden of describing return contents. Combined with annotations that cover the safety profile and default idempotency, an agent has what it needs to invoke it, though error behavior for a missing slug is unaddressed.

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 parameter with 0% schema description coverage, so the schema only conveys type, length, and pattern. The description contributes the key semantic that the slug must be exact (not a fuzzy match), but adds no format or normalization guidance beyond that.

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 ('catalog product') plus the lookup key ('by exact slug'), and the enumeration of returned fields further pins down the resource. It does not name search_agents as the non-exact alternative, so the sibling distinction is only implied by 'exact slug'.

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?

'By exact slug' implies the caller must already know the identifier and that fuzzy/partial lookup belongs elsewhere, which is usable implied guidance. However, it never states when to prefer search_agents or what to do without an exact slug, so no explicit alternative routing is provided.

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, closed-world and non-destructive, so the safety profile is covered. The description adds behavioral context the annotations do not: the field set returned and the non-obvious fact that every listed task has at least three catalog candidates. It stops short of describing pagination or result ordering.

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 sentences, front-loaded with the verb and resource, then the optional filter. The middle sentence about "at least three catalog candidates" is specific but of uncertain relevance to selection, slightly diluting an otherwise tight definition.

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 compensates by naming the fields returned, and the annotations cover the read-only/idempotent profile. For a zero-required-parameter listing tool this is close to complete, though return shape (ordering, volume) is not described.

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%, but the single parameter is a self-documenting enum of eight categories. The description confirms the filter is optional ("Optionally filter tasks by category"), which matches the schema's non-required status but adds no syntax or semantics beyond what the enum already conveys. Baseline 3 is appropriate.

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 states a specific verb and resource ("List Agenlify task IDs") and enumerates the payload fields returned: preparation checklists, expected outputs and review requirements. Sibling differentiation is not addressed, but the siblings (get_agent, search_agents) operate on a different resource entirely, so confusion is unlikely. Clear and specific, just no explicit routing language.

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 tool returns a task catalog with an optional category filter, which suggests it is the discovery entry point for tasks. There is no statement of when to use it versus alternatives, and no prerequisites or exclusions. Adequate but with a clear gap.

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 value beyond them by disclosing the return shape (dated catalog summaries and source links) and the interpretation of empty results, which an agent needs to reason about outcomes.

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 dense sentences, no filler, with the core search scope front-loaded and the return/empty-result semantics trailing. Every clause (language scope, filter axes, return content, empty meaning) 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?

With no output schema, the description steps in to describe returns (dated summaries plus source links) and the empty-result case, which is exactly what's needed. The only shortfall is that the pagination/limit params are left uncovered for an 8-parameter 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 only 25%, so the description must compensate and largely does: it explains that query accepts a task, product name or official domain in English or Chinese, and maps the pricing/setup/category/task/evidence filters. Only limit and offset go unexplained in both schema and description.

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 (search) plus resource (public Agenlify catalog) and the match modes (English/Chinese task, product name, official domain), and enumerates the filter axes. It is clearly distinguishable from get_agent (single-item fetch) and list_tasks, though it never names those siblings 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?

Usage is only implied through the filter list; the description does note that an empty query lists products and that empty results mean no documented match, which is useful context. However, it gives no explicit when-to-use-this vs get_agent/list_tasks guidance or exclusions.

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