Jensing

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

The annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered elsewhere. The description adds one useful behavioral fact — that the full article body is returned rather than a match excerpt — but says nothing about failure behavior for a missing id or about the no-output-schema return shape.

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 zero filler, front-loading verb, scope, and the provenance of the required argument. Nothing repeats the title or restates the schema.

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 two-parameter read-only lookup with full schema coverage and complete annotations, the definition covers everything essential: what is retrieved, at what granularity, and where the id originates. Only minor edge-case behavior for invalid ids is unaddressed, and it is not required by the structured fields.

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%, so the baseline is 3, but the description adds provenance the schema lacks: it tells the agent the id is the one produced by search_knowledge, which is real guidance for constructing a valid call. The language parameter and its effect on the returned text are left entirely to the schema.

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 gives a specific verb and resource ("Read one article in full") and scopes it precisely to fetching a single item by id, which is clearly distinct from the sibling search_knowledge that produces those ids. An agent can tell this apart from list_companies or get_company without opening the 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?

It establishes the intended workflow by saying the id comes from search_knowledge, which tells the agent when this tool follows another call. It stops short of an explicit exclusion (e.g., that search_knowledge returns snippets only and this returns full text) or what to do if the id is unknown, so it sits just below the top score.

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=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered elsewhere. The description adds only the slug-provenance relationship to list_companies, saying nothing about response shape, error behavior for unknown slugs, or localization effects beyond the schema's 'Language of the answer'.

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 tight sentence with the scope and the slug source front-loaded; no redundant restatement of the name or title and nothing to trim.

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 two-parameter read tool with rich annotations, the definition covers what it does and where the identifier comes from. With no output schema, it could say slightly more about what 'read about' returns, but the gap is small for this complexity level.

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%, so both parameters are already documented, including the language enum with its default. The description's only added meaning is that the slug originates from list_companies, which is useful but marginal over the structured data.

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 ('Read about one company') with explicit singular scope, and distinguishes itself from the sibling list_companies by tying its input to that tool's output. An agent can tell immediately this is the detail-fetch counterpart to the list tool.

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 the slug list_companies returned' gives a clear usage path: call list_companies first, then fetch details here. It lacks explicit exclusions (e.g., when to use search_knowledge or get_article instead), which keeps it from a 5.

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=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful content about the return payload (email, form, who answers) but says nothing about freshness, rate limits, or how the contact details are sourced.

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, front-loaded with what is returned before the when-to-use clause. Slight redundancy with the title ("Jensing") but nothing wasteful.

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-only lookup with no output schema, the description is adequate: it tells the agent both the trigger and roughly what the answer contains. Minor gap is that it never states localization behavior for the language parameter.

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 there is a single optional language parameter, so the schema already carries the semantics. The description adds no information about the language option (e.g. that the answer is localized), so 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?

The description uses a concrete verb plus enumerated resources ("Get the email address, the enquiry form and who answers"), so an agent knows exactly what comes back. It does not explicitly distinguish itself from siblings like get_company or search_knowledge, but the contact-channel framing is distinct enough in practice.

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?

"For when the user wants to talk to Jensing" gives a clear triggering condition for selection. It stops short of naming an alternative tool or stating when not to use it, which keeps it from a 5.

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 behavior, so the bar is lower. The description adds that results include industry, stage, and a one-line description, and 'on jensing.com' is consistent with openWorldHint=false. It says nothing about result volume, ordering, or whether the whole set is returned in one call — notable gaps for a list tool with no pagination parameter.

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 well-formed sentence with the resource and scope front-loaded and no wasted words. It is arguably too terse rather than bloated, but structurally clean.

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 two-parameter read-only list tool with full schema coverage and no output schema, the description covers the resource, scope, and the shape of returned records. Missing details about ordering and result-set size are minor rather than blocking.

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%, so both parameters are already documented; baseline 3 applies. The description's mention of 'industry' is ambiguous — it reads as a returned field rather than clarifying the industry filter — and the language parameter is not referenced at all.

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 gives a specific verb and resource ("List the companies") and scopes it to jensing.com, plus hints at the returned fields. It does not explicitly distinguish itself from the sibling get_company, which returns a single company, so differentiation is left to inference.

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: 'List' signals a full enumeration versus get_company for one record, but the description never states when to use this instead of get_company or search_knowledge. No prerequisites or exclusions are given.

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, closed-world, so safety needs no restating. The description adds behavior the annotations cannot: retrieval is semantic rather than keyword-based, queries may be in any language, and the response is an answer rather than a raw record fetch. It omits failure and low-confidence behavior, which keeps it off a 5.

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 with no filler. The subject matter is front-loaded in a scannable list, and the behavioral note about semantic search follows the scope. Nothing repeats the schema or the title.

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?

This is a two-parameter read tool, and the description covers scope, retrieval mode, and query phrasing adequately for an agent to call it confidently. With no output schema, a brief note on what comes back (a synthesized answer with sources, or a list of passages) would close the only real 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?

Schema coverage is 100%, so the baseline is 3, and the description earns above that by clarifying that a query may be written in any language while the separate language parameter selects the language of the answer rather than constraining the query. That distinction is easy to get wrong and is not spelled out in the schema. It does not mention the 200-character cap or give example phrasings, so it is not a 5.

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 gives a specific verb ("find answers") tied to a specific corpus (Jensing knowledge) and enumerates the topic areas covered: who it helps, problems solved, getting started, cost and funding, approvals, track record, origin. That is meaningfully more specific than the title alone. It stops short of naming a sibling, so an agent still has to infer that get_article fetches a known document while this tool discovers unknown ones.

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?

"Searches by meaning, so ask in plain words, in any language" tells the agent how to phrase a query, which is genuine usage guidance. It never says when to reach for this instead of get_article or get_company, nor does it state what to do when no confident match exists. Usage is implied by the topic list rather than stated as a routing rule.

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