Psychologie & Sérénité

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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false), so the description's contribution is the return-content disclosure: which fields exist, that the address is given twice (official and provenance-tracked), and that language coverage varies by service. It omits what happens with an unknown service identifier and offers no note on response locale, which keeps it short of 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?

A single front-loaded sentence with the verb first, then the payload details in order of importance. The parentheticals (language counts, PSW/PT/ScanMyLove examples) all carry information rather than padding.

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 must carry the return-value burden; it names the main content categories but not the response shape or structure. For a one-parameter read tool this is adequate, but the coverage of outputs is a list of topics rather than a usable contract.

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 single enum parameter is documented as 'Identifiant du service (voir list_services)'. The description adds no mapping between the cryptic enum values (sml, smj, salon_psy) and the product names it mentions (PSW, PT, ScanMyLove), so the 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?

A specific verb and resource ('Décrit un service en détail') followed by an enumeration of what the description returns: official address, provenance-tracked address, per-language variants, reference pricing in euros, and francophone targeting for video appointments. It is clearly distinct from list_services and the get_* siblings in intent, 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?

The description gives no when-to-use guidance, no conditions for preferring describe_service over list_services, and no prerequisites. The only routing hint ('voir list_services') lives in the input schema, not the description.

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, so the safety profile is covered. The description usefully adds output characteristics (Markdown, CC-BY 4.0 license, fr/en content) but says nothing about lookup failure behavior or truncation for long articles.

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 that states resource, return format, license and language with zero redundancy. Every element 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?

For a simple two-parameter read tool with no output schema and annotations that already cover safety, the description supplies the key return-value context (format, license, languages). Only edge-case behavior (unknown slug, very long articles) is absent.

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 carry the load. It partially compensates by implying the locale dimension ('en français ou en anglais'), which maps to the fr/en enum, but the required 'slug' parameter (maxLength 220) is never explained or exemplified.

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 resource ('Texte complet d'un article du blog') and qualifies the return format (Markdown) and license, which is well beyond a tautology. It implies it differs from search_articles by promising the full text, but never names the sibling or contrasts 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?

There is no statement of when to use this tool versus the sibling search_articles, nor any prerequisite about needing a known slug. Usage is only inferable from the name and the word 'complet'.

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?

The annotations already cover readOnly, idempotent, non-destructive and openWorld, so the safety profile is settled, and the description adds the content contract: what a response actually contains (presentation, themes, formats, price, page count, purchase and extract links). The explicit 'Pas de texte intégral' exclusion is real behavioural disclosure, because it stops an agent from treating this as a content-retrieval tool. It omits pagination or any state about the call itself, which caps the score at 4.

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?

The whole definition is one front-loaded sentence introduced by a clear label, with no filler. It is dense, with a nested parenthesis enumerating formats and price details, but everything listed earns its place because there is no output schema to carry the return shape.

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 no output schema, the description adequately covers the return shape: themes, available formats, reference price in euros, page count, purchase and extract links. The one real gap is how the required slug is obtained. Annotations already cover the safety profile, so that gap does not sink overall completeness.

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 50%, and the parameter that the schema does not document is the required one, 'slug': nothing in the schema or the description says what a slug is or where to find it. The description mentions no parameter at all, though it does imply that the returned fare includes a page link. With the required identifier undocumented in both places, the description does not compensate for the coverage gap.

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 resource (a book fact sheet) and enumerates its parts: presentation, themes, commercial offer (formats, reference price in euros and page count), a link to the purchase page, and a link to the free extract. It is unmistakably a detail/fetch tool rather than the list/search tool. However, it does not name the sibling it differs from; an agent still has to infer that search_books supplies the 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?

The closing note 'Pas de texte intégral' effectively tells the agent when not to call the tool if it needs the full text, which is useful. But there is no positive context for when to use it (e.g. 'call once you have a slug from search_books') and no named alternative for full-text needs. Usage is only implied by the shape of the description.

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, openWorldHint, and destructiveHint=false, so safety is covered. The description adds that the output is a link and clarifies the two report types, but says nothing about what the link opens or any access conditions.

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 efficient sentence that front-loads the return type ('Lien vers un exemple de rapport') and then enumerates the two variants. No wasted text.

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 link-returning tool with no output schema and no required parameters, the description adequately explains what is returned and the two service modes. Minor gaps around locale behavior are covered by the schema.

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 75%, with detailed descriptions for `locale` and `langue_sml`. The description only implicitly maps `slug`/`service` to the two report modes; it adds little beyond the schema for the remaining parameters. Baseline 3 is appropriate given the high coverage.

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 it returns a link to an example report, with two variants: a test example page or the ScanMyLove demo report. This distinguishes it from siblings like get_test or get_article, though the phrasing is nominal rather than verb-first.

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 two modes (test example page vs. ScanMyLove demo) imply when to use each, but there is no explicit guidance on when to choose this tool over get_test or other report-related siblings. The `service` distinction 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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds only a scope caveat about what is not returned; it says nothing about error behavior for an invalid category/slug or lookup failure.

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 efficient sentence with the content summary front-loaded, followed by a short exclusion clause. No filler, though it is terse enough that the exclusion clause carries more structural weight than its content justifies.

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 read-only fetch with no output schema, the description sketches the returned fields and rules out questionnaire/results content. Combined with rich annotations and mostly documented parameters, an agent has enough to call it correctly; only failure modes remain 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?

Schema coverage is 67%: locale and category carry full descriptions (including a cross-reference to search_tests and locale fallback behavior), while slug is undocumented but self-evident. The description adds no parameter meaning of its own, 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 a specific resource (the detail sheet for one test) and enumerates what it contains: presentation, measured dimensions, duration. The closing clause ('Aucune question ni aucun résultat') distinguishes it from siblings like start_test and get_example_report, though the verb is implicit rather than explicit.

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 via negative scoping: 'no questions, no results' hints that start_test and get_example_report are the tools for those needs, but no alternative is named and no when-to-use condition is stated. 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, openWorldHint and destructiveHint=false, so the safety profile is fully covered externally. The description adds genuinely useful context beyond them – that the result includes each service's languages and reference prices in euros – but says nothing about result size, completeness guarantees or how a consumer should page/iterate over the catalogue.

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 verb and resource, with no filler. The long parenthetical enumeration of service names is informative but heavy, making the sentence harder to scan than a short list would be.

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 must convey what comes back, and it does specify services, their languages and euro-denominated reference prices. For a zero-parameter, read-only catalogue tool this is largely sufficient, with only result shape/ordering left unspecified.

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 there is nothing to disambiguate and the baseline of 4 applies. The description correctly implies an unfiltered full dump rather than a parameterized query.

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 ("Liste") and a scoped resource ("tous les services de Psychologie & Sérénité"), then enumerates the concrete service types so the agent knows exactly what catalogue is covered. The plural/whole-catalogue framing implicitly separates it from the singular sibling describe_service, though it never names that sibling.

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 explicit when-to-use or when-not guidance and no reference to alternatives such as describe_service for per-service detail. The agent must infer from the plural verb that this is the entry-point catalogue lookup, which is implied at best.

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, openWorldHint and non-destructive, so the safety profile is covered. The description adds genuine value beyond annotations by disclosing the return shape (titres, résumés, liens) and the unsearchable es/pt corpus, but stays silent on pagination and the interaction with the limit cap.

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 tight sentences: purpose, return values, then the language caveat, front-loaded with the primary function. No filler, though the corpus-size figures are borderline colour rather than operational 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 simple read-only search with no output schema, the description covers the essentials an agent needs: what is searched, what comes back (titles, summaries, links), and the language-coverage caveat. The gap is the absence of any guidance on the limit/query parameters, which the schema leaves bare.

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 only 33% — just 'locale' is documented, and its schema text already explains the fr/en/es/pt behaviour in more detail than the description. The description adds nothing about 'query' (syntax, matching) or 'limit' (default 10, max 30), so it fails to compensate for the undocumented parameters.

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 ('Cherche dans le blog') and quantifies the corpus (1 500+ FR, as many EN), which distinguishes it from the sibling search_books, search_concepts and search_tests by making the 'articles/blog' scope explicit. It stops short of naming those siblings directly, so differentiation relies on 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?

Provides a partial when-not by stating the es/pt pages are 'non cherchables ici', which scopes the tool, but gives no positive guidance on when to prefer search_articles over get_article or the other search_* tools. Usage is implied rather than instructed.

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, openWorldHint and destructiveHint=false, so the safety profile needs no restating. The description adds genuinely useful context by disclosing that only catalogue records are returned and which languages exist, but it says nothing about result ordering, how the limit truncates results, or what a record contains.

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 with the scope limitation front-loaded in the parenthetical, so the most decision-relevant fact lands first. Nothing is redundant, though the language enumeration overlaps with 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 4-parameter search tool with no output schema and sparse parameter documentation, the description covers what the tool returns at a coarse level (fiches, not full books) but not enough to predict result shape, ranking, or the effect of combining query with topic. Adequate, but clear gaps remain for a tool whose schema carries little explanation.

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 only 25% (locale alone is documented), so the description needs to compensate for query, topic and limit — and it does not. Its language sentence ('Les fiches existent en fr, en, es, pt') largely duplicates what the locale enum and its schema description already provide, leaving query/topic interaction and the limit default of 6 unexplained.

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 ('Cherche dans le catalogue de livres') and immediately bounds the scope with 'fiches uniquement : le livre entier n'est pas accessible ici', which implicitly separates it from the get_book sibling. It stops short of naming the alternative tool 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 implied rather than stated: the parenthetical tells the agent that full-book retrieval is not possible here, which nudges toward get_book, but there is no explicit 'use this when…' or 'use X instead for…'. The agent must infer the routing rule from the scope note.

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, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds nothing behavioral beyond that: no mention of result format, ranking, pagination, or what happens on an empty query.

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 a single tight sentence with no filler, but the brevity stems from under-specification rather than economy: the fragment omits the verb and any usage or parameter information.

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 search tool with no output schema and two undocumented parameters, the description is too thin. It does not convey what a call returns or how search behaves, so an agent cannot confidently invoke it versus sibling search tools.

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% for both 'query' and 'limit', so the description carries the full burden and does not compensate. It never explains that 'query' is a free-text search term or what 'limit' controls, though the examples hint at the queryable subject matter.

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 domain ('concepts et modèles cliniques') and gives concrete examples (attachement, Gottman, schémas de Young), which loosely distinguishes it from the article/book/test searchers. However it is a noun phrase with no verb, never stating that it performs a search, so an agent must infer the action from the tool name.

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 indication of when to choose this tool over search_articles, search_books, or search_tests, nor any prerequisites or exclusion conditions. The sentence only describes content, leaving routing entirely 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 readOnly, idempotent, non-destructive and openWorld, so the safety profile is covered. The description adds genuinely new context by stating what the tool does NOT return ("Ne renvoie ni questions ni résultats"), which prevents an agent from expecting test items or scores. It stops short of describing pagination or ordering behaviour.

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 short, front-loaded sentences: what is searched, how it filters, what it does not return. No filler and no repetition of 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?

For a 4-parameter, no-output-schema search tool, the definition covers scope, filter mechanism and the key negative about return content, which is the main ambiguity an agent would face. It could still say more about result shape or how limit interacts with the 206-item corpus, but nothing essential for correct invocation is missing.

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 75%: query, category and locale carry their own descriptions (locale quite thoroughly). The description only echoes keywords and theme, adding the combinability nuance but saying nothing about limit or how category slugs relate to free-text query. With the schema doing most of the work, the 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 gives a specific verb ("Cherche") plus the resource and its scope ("206 tests psychologiques (fiches)"), which cleanly separates it from the singular get_test and from search_articles/search_books. It does not explicitly name a sibling to contrast with, so it stops short of a 5.

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?

"Filtre par mots-clés et/ou thème" implies how the tool is used, and the phrase "et/ou" signals the filters are combinable. But there is no explicit statement of when to pick this over get_test (browse/search vs. fetch one known sheet), so usage is only implied.

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, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: the returned link is anonymous with no account, and the actual test pass, level scoring and paid report all happen off-conversation on the website, which tells the agent this call is a gateway, not an executor.

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 what the tool produces, followed by the one non-obvious fact (the workflow continues outside the conversation). Nothing is redundant with the title or annotations.

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 correctly states that the return is a link and that everything downstream happens on the site, which is the key thing an agent needs. It could go slightly further on whether the link is one-time or shareable, but the essentials are present.

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 slug and locale are already documented in the schema (including the language fallback nuance). The description adds no parameter-level detail, so the baseline of 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 and resource: it returns the link to take a test, and clarifies the test is anonymous and account-free. However it never names or contrasts with close siblings like get_test or search_tests, so an agent gets the purpose but must infer the boundary itself.

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 usage (anonymous test-taking) but never states when to pick this over get_test or search_tests. The note that execution happens on the site rather than in conversation is useful context, but it is a workflow fact, not an explicit use/when-not-to-use rule.

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