workonit

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 fully covered structurally. The description adds the payload scope (three sites, company, llms.txt/OpenAPI links), which is genuinely useful context about what is returned, but nothing about format, size, or side effects beyond that.

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 highest-value content up front (what the tool is about, then the three payload components). It is terse to the point of being a fragment rather than a sentence, but nothing is wasted.

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 trivial read-only, zero-required-parameter orientation tool with full schema coverage and no output schema, the description covers purpose and return scope adequately. What is missing is minor: the response shape or ordering, and any hint that omitting 'site' returns all three.

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 100% and the single 'site' parameter is documented in the schema with its enum values and the filtering behavior ('מחזיר רק את האתר הזה'). The description only alludes to this via 'שלושת האתרים' and adds no syntax or default semantics, so the schema does the work — baseline 3.

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 resource ('workonit') and enumerates what comes back: the three sites, the company behind them, and links to llms.txt and OpenAPI. That is specific enough to separate it from the list_* siblings, which enumerate entities rather than explain the product. The verb is only implicit ('מה זה' / get info), so it falls short of a clean verb+resource statement.

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: an agent can infer this is the orientation/overview call, plausibly the one to make before the list_* tools. There is no explicit 'use this when…' or 'do not use this for…' and no mention of when to prefer list_apps or list_ai_agents instead.

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 the safety profile is fully covered elsewhere. The description adds genuinely new context: what fields come back and that the main agent comes first. It does not disclose whether the list is filtered by store visibility rules or whether results are paginated.

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 short sentences with no filler: the first names the resource and returned fields, the second conveys ordering. Front-loaded on the resource. Only minor weakness is that the ordering sentence is somewhat terse and could be folded in more explicitly.

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?

A single optional parameter and no output schema means the description's job is small, and it covers what is returned and in what order. The only gap is not stating that an empty query returns all agents, which would matter given the parameter is optional.

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 100% and the single 'query' parameter is documented in the schema as a partial-name filter. The description adds nothing about the parameter, which is acceptable at full coverage but means no value beyond the schema. Baseline 3 applies.

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: lists the AI agents exposed in the workonit store, and adds what each entry carries (name and description). It also describes the ordering ('the main one, followed by its specialists'), which lets an agent predict the shape of the list. It does not name a sibling to distinguish from, but the siblings (get_workonit_info, list_apps) are clearly different resources.

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 rather than stated: the tool returns store-visible agents, so an agent can infer this is the discovery call for AI agents. There is no explicit when-to-use, no when-not-to-use, and no mention of the sibling tools as alternatives. Adequate but leaves routing 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 readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds useful non-annotation context: results are limited to discoverable store apps, each returned with name and description, sorted by name.

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 compact sentence that front-loads the resource and packs scope, returned fields and ordering. No filler, though the ordering phrase 'לפי השם' is slightly ambiguous against the 'query' param.

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, and the description compensates by naming the returned fields (name and description) and the sort order. The only gap is behavior on empty results or result-set size, which matters less for a single-param read-only listing.

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 100%, and the schema already explains the 'query' substring filter fully. The description says 'לפי השם' (by name), which reads more as an ordering hint than a parameter explanation, so it adds little beyond the schema. Baseline 3 applies.

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 ('האפליקציות שגלויות בחנות של workonit') with the scope 'visible in the store' and ordering. Siblings (get_workonit_info, list_ai_agents) cover different resources, so the distinction is implicit 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?

Usage is only implied by the word 'list' – there is no explicit guidance on when to use this versus list_ai_agents or get_workonit_info. No exclusions or prerequisites are given, though the tool is simple enough that inference is easy.

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