MissCV: CV, plantillas y entrevistas

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

Annotations already declare this a safe, idempotent, read-only query, so safety is covered. The description adds genuinely useful behavioral context by disclosing the conditional branching: without a tool it returns categories rather than results.

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, front-loaded with the core purpose and ending with the fallback behavior. Every clause carries information; nothing is redundant.

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 single-parameter read tool with full annotation coverage and no output schema, the description conveys enough about what is returned (alternatives or categories). Return shape/format is left unspecified, but that is a minor gap here.

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 documents the parameter as an optional paid-tool name. The description goes further by spelling out the semantic consequence of supplying vs. omitting it (alternatives vs. categories), adding meaning beyond 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?

States a specific verb (devuelve) and resource (alternativas gratuitas a herramientas de pago para buscar trabajo), with concrete examples of the tools covered. No sibling tool overlaps this lookup function, so the scope is unmistakable.

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?

Explains the key usage branches: pass a tool to get its alternatives, or omit it to get the available categories. It gives clear context for invocation, though it doesn't reference any sibling tool as an alternative or state exclusions.

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 (readOnly, idempotent, non-destructive). The description adds real behavioral context beyond that: the tool only hands back a link, the analysis is performed externally, and it explicitly does not receive or read any CV, which prevents an agent from assuming it does the analysis.

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 sentences, front-loaded with what is returned, followed by the crucial clarification that the analysis is external. No filler; each sentence removes a potential misunderstanding.

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 input parameters and no output schema, the description carries the burden and does so adequately: it states what comes back (a link plus what the person receives) and how the flow works. Minor gap in not describing the link's format or destination, but nothing critical 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?

The tool takes zero parameters, so the schema carries no semantics to compensate for. Baseline 4 applies; there is nothing for the description to clarify on 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?

States a specific verb and resource: it returns the link to analyze a CV on MissCV plus what the person receives. It also draws a clear boundary ('el análisis no ocurre en el chat'), which helps separate it from siblings, though no sibling is named 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?

Explains the actual usage flow: the analysis happens off-chat, the person uploads their CV at the returned link. This tells an agent when and how the tool fits the conversation, but it never names an alternative tool or a when-not-to-use condition.

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 closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the result cap of up to 8 and what each result contains (descripción y enlace de descarga).

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 waste; the core purpose and source are front-loaded, with category examples and the return shape following. Every clause 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 supplies the missing return information (up to 8 templates, each with description and download link). For a single-parameter read-only search tool whose annotations cover safety, nothing needed to call it correctly 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 100% and the single parameter is already documented with examples in the schema. The description restates the searchable dimensions (estilo, nivel, rol) and adds slightly more examples, but adds no syntax or format detail beyond the schema baseline.

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 (busca) and resource (plantillas de CV en Word) with the scope of the source catalog (MissCV gratuito) and the facets it searches on (estilo, nivel, rol). The category examples make it unmistakable against siblings like search or alternativas_gratis.

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 usage context is implied by the description (search templates by style/level/role), but there is no explicit when-to-use, when-not-to-use, or naming of an alternative sibling such as search. Nothing guides the agent to this tool over a generic search.

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, non-destructive and closed-world, so the safety profile is covered. The description adds the useful fact that the response contains 'texto completo para adaptar', i.e. full adaptable text rather than just references, but says nothing about response size or caching.

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 front-loaded sentence that leads with the return payload and purpose. Slightly padded by enumerating all five enum values, which the schema already exposes, but it costs little space.

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 single-parameter, read-only lookup with no output schema, the definition is close to sufficient: it identifies the resource and confirms that full text is returned. The remaining gap is routing versus 'buscar_plantilla', which an agent would have to guess.

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 'tipo' parameter is a fully-documented enum, so the schema does the heavy lifting. The description's list of document types merely restates the enum values rather than adding format or selection guidance beyond them, 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?

States a specific verb (Devuelve) and resource (modelos de un documento laboral) and enumerates the five document types, so the agent knows exactly what comes back. It does not, however, differentiate itself from the sibling 'buscar_plantilla', which plausibly covers overlapping ground.

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 says what is returned but never states when to choose this tool over alternatives such as 'buscar_plantilla', nor any prerequisite (e.g., that the 'tipo' must be one of the supported types). Usage is only implied by the enumeration.

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 needs no repetition. The description earns credit for disclosing the return shape (text with title, URL, date), which is valuable since there is no output schema. It omits auth/permission requirements, which is a minor 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?

Two sentences, zero filler, and the return-value disclosure is front-loaded ahead of the accepted input formats. Nothing needs trimming.

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 single-parameter read tool with annotations covering safety and no output schema, the description supplies everything an agent needs: what comes back, what input shapes are accepted, and its relationship to search. No material gap remains.

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 description for 'id' already says it is a search id, path, or misscv.com URL. The description restates the same three accepted forms and only marginally adds the '/blog/...' path example, 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?

States a specific action (returns a public MissCV page as text) plus the exact payload contents (title, URL, date). This clearly separates it from the sibling search tool, whose output id it consumes, so an agent can distinguish read-the-page from find-the-page without opening either 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 tells the agent when this tool fits: after search, since it accepts the id that search produces, or alternatively a path/URL. There is no explicit when-not-to-use or named alternative, but the placement in the search→fetch workflow is unambiguous.

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, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds genuine context beyond that by disclosing the output contents (skills plus a written example plus an ATS-filter flag) and the data source (banco de habilidades de MissCV). It does not mention any rate limits or cost, which keeps it below 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?

One sentence, front-loaded with the return payload before the provenance note. No filler, though the trailing 'Sale del banco de habilidades publicado en MissCV' is closer to branding than operational 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 one-parameter, read-only lookup with no output schema, the description is adequately complete: it conveys what comes back (skills, example phrasing, ATS relevance) so the agent knows what to expect. It stops short of explaining matching behavior when the role string is ambiguous or unknown.

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 a single parameter with 100% schema description coverage, and the schema already gives the meaning and examples («ventas», «enfermería», «contador»). The description restates the idea with 'según el oficio o el rol' but adds no syntax, granularity or matching behavior 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 (devuelve) and a precisely scoped resource: habilidades técnicas y blandas para el CV según el oficio/rol, además del ejemplo de redacción y el indicador ATS. That specificity separates it naturally from siblings like preguntas_de_entrevista or analizar_mi_cv, which cover different stages of the job-search workflow.

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 for building the skills section of a CV for a given role. There is no explicit when-to-use, no when-not-to-use, and no named alternative (e.g. buscar_plantilla for templates or analizar_mi_cv for reviewing an existing CV).

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 by structured data. The description adds no further behavioral detail such as freshness of pricing, caching, or localization of the returned policy text, so it adds little beyond the annotations.

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 zero filler. The content of the response is front-loaded and the use case is appended second, which is the right ordering for scanning.

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 and no parameters, the description carries the return-value burden and does so by enumerating the covered topics (free tier, Pro features, price, refund, cancellation). An agent knows exactly what it will get back and whether it answers a pricing question.

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 for the description to disambiguate; the baseline for a parameterless tool applies. No parameter-related gaps exist.

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 concrete verb and resource ('Devuelve los planes publicados de MissCV') and enumerates what the payload covers: free tier, Pro contents, published price, refund, and cancellation. The scope is clear enough to separate it from the sibling 'alternativas_gratis' (which concerns other free options rather than MissCV's own plans), though no sibling is named 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?

'Sirve para preguntas sobre cuánto cuesta MissCV' gives an explicit triggering context for when to call this tool. It stops short of stating exclusions or naming an alternative for adjacent questions (e.g. free alternatives to MissCV), so it is clear but not fully routing.

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, idempotentHint=true, destructiveHint=false), so the bar is lower. The description still adds real behavioral content beyond them: the output is questions paired with an answer tip, grouped by theme, and the no-argument fallback returns one per theme. It does not disclose volume or 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?

Three short sentences, front-loaded with the output shape and ending with the fallback behavior. Slight redundancy with the title ('Preguntas de entrevista con consejos') but no filler or 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 compensates by describing the return content (question + tip, ordered by theme), and the single optional parameter is fully covered by the schema. Nothing essential to correct invocation is missing, though result volume remains 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?

Schema coverage is 100% and the single optional parameter is documented, so baseline is 3. The description goes further by naming additional valid themes (fortalezas y debilidades, trabajo remoto, preguntas incómodas) beyond the schema's examples and by defining the semantics of omitting 'tema', which the schema does not state.

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 ('Devuelve preguntas de entrevista de trabajo con un consejo para responder cada una') plus the organizing dimension (tema). It is clearly distinguishable from siblings like analizar_mi_cv or buscar_plantilla, though it never explicitly names an alternative 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 description gives one implicit usage cue — omitting 'tema' returns one question per category — which tells the agent how to invoke it, but it never states when to prefer this tool over siblings or what conditions make it inappropriate.

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 safety is covered. The description adds genuinely new behavioral context: a hard cap of up to 10 results, the fields returned (id, título, URL), and the follow-up read path via fetch. It does not mention ranking, language, or whether results can be empty.

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, zero padding, with the content scope front-loaded and the read-next instruction placed last. Every clause either defines the searchable corpus or explains the return and follow-up, so 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?

With no output schema, the description usefully documents the return shape and the 10-result cap, and it sets up the fetch handoff. Minor gaps remain (result ordering, pagination or lack thereof, empty-result behavior), but an agent has enough to invoke it correctly.

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 already documented in Spanish with an example ("carta de renuncia"). The description adds no parameter-level detail beyond what the schema provides, 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?

States a specific verb and resource ("Busca en las páginas públicas de MissCV") and enumerates the corpus it covers: guías, plantillas, documentos laborales, habilidades por oficio y artículos del blog. It also distinguishes itself from the sibling fetch by explaining that fetch is for reading a result in full. An agent can tell exactly what this tool returns 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?

The description routes the agent explicitly: search here for public pages, then use the returned id with fetch to read a full document. That covers the primary alternative-tool decision, but there is no stated exclusion (e.g. what this does not search, such as private/user content) or mention of the other similarly named siblings like buscar_plantilla.

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