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

Annotations already declare readOnly/idempotent/openWorld and the safety profile, but the description adds the non-obvious behavior that results carry a computed opportunity score across five factors, and that it reads only the public listing. Rate-limit/scraping details live in the schema, not here, so it is not fully self-contained.

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 tightly written sentences: the first front-loads purpose plus the scoring behavior, the second handles scope and the alternative. No filler, and the most decision-relevant content comes first.

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 an output schema present, return values need not be described, and the annotations plus the description cover the safety and scope profile. The only gap is that it does not point to the remaining sibling tools or note result volume limits, which the schema partially covers.

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 the schema already documents all 16 parameters with enums, defaults, and semantics (e.g. max_consultas explains the request-splitting behavior). The description adds no parameter-level detail beyond loosely naming the scoring factors, 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 (Busca), resource (proyectos abiertos en Workana), and an added behavior (scoring 0-100 by fit/competition/budget/client/freshness). It explicitly names the sibling workana_evaluar_proyecto as the tool for client data, so an agent can distinguish it 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?

Names a concrete alternative and the condition that routes to it ('para datos del cliente... usa workana_evaluar_proyecto') and scopes the tool with 'Solo lee el listado público'. It does not mention the other siblings (workana_mejores_oportunidades, workana_ver_proyecto), so guidance is strong but not exhaustive.

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 goes further by disclosing what the analysis actually surfaces — scoring dimensions and specific risk alerts such as off-platform payment, unpaid work and WhatsApp contact — which is genuine behavioral context 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?

A single front-loaded sentence that names the action first and then packs the scoring dimensions and alert types into a tight parenthetical list. Dense but every clause carries information; nothing is 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?

An output schema exists, yet the description still communicates the shape of the result (score, breakdown, alerts, advice), and annotations cover the safety profile. The one gap is routing guidance relative to its siblings, so an agent knows when this analysis is warranted versus a plain project fetch.

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%: 'proyecto', 'mis_skills' (with default-profile fallback) and 'formato' are all documented in the schema itself. The description adds no parameter-level detail, so the baseline 3 applies — the schema does the heavy lifting.

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 ('Analiza a fondo un proyecto') and enumerates the concrete output: a 0-100 score with a breakdown across five dimensions, alerts, pros/cons and proposal tips. That is far more specific than a bare title, though it never explicitly contrasts itself with siblings like workana_ver_proyecto or workana_mejores_oportunidades.

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: it's clearly the 'should I apply?' tool, which sits after ver_proyecto and alongside mejores_oportunidades. But there is no explicit when-to-use, when-not-to-use, or named alternative, leaving the agent to infer the routing from the sibling names alone.

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 establish the safe, read-only, idempotent, open-world profile. The description goes beyond them by disclosing what the deep analysis actually does — it pulls the client's payment history and returns score-ordered results with alerts and tips, and it filters out low-budget / high-competition listings. It does not mention cost/time behavior, but that lives in the schema.

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, front-loaded with the action sequence and closed with the use case. No filler, and the ordered pipeline structure mirrors how the tool actually executes.

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 an output schema present, return values need not be re-explained, and the description still usefully notes the ranking and alert content. For a 12-parameter, session-dependent scraping tool the remaining gaps (pagination cost, session caveats) are covered by the schema, so the description is nearly complete.

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 all 12 parameters are already documented by the schema; baseline is 3. The description adds only a loose conceptual mapping ('mejores N' -> top, the 'presupuesto bajo / demasiada competencia' filter -> presupuesto_min_usd / max_propuestas) without adding syntax or format detail.

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 composite verb chain — search recent projects, discard bad ones, deeply analyze the best N, return them ranked — so an agent understands this is an orchestrating pipeline rather than a single lookup. It differentiates from the granular siblings (buscar/ver/evaluar) only implicitly by calling itself a 'flujo completo', but never names them.

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 gives a clear usage context ('Flujo completo para el día... Ideal para una revisión diaria'), which tells the agent this is a broad daily-sweep call. However, with three directly related siblings it never explains when to prefer workana_buscar_proyectos or workana_evaluar_proyecto instead, so the routing decision is left 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 structurally. The description adds only a catalog of returned fields and no behavioral context such as rate limits, auth requirements, or whether missing projects error out.

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 leads with the core purpose and then enumerates contents without filler. It is appropriately sized, though the long field inventory borders on restating the output 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?

With an output schema present, the description need not explain return values, and the annotations cover the safety profile, so it is largely complete for a read-only viewer. The enumeration of returned fields is somewhat redundant with the output schema, 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?

Schema description coverage is 100%: the schema already documents 'proyecto' as a URL or slug and 'formato' as markdown/json. The description adds no syntax, format, or default guidance 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+resource (ver/ficha completa de un proyecto) and enumerates exactly what the record contains (descripción, skills, presupuesto, propuestas, freelancers, datos del cliente). It is immediately clear what the tool returns, but it never distinguishes itself from siblings like workana_evaluar_proyecto or workana_buscar_proyectos.

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 when-to-use, when-not-to-use, or alternative routing guidance. It does not tell the agent to prefer workana_evaluar_proyecto for scoring or workana_buscar_proyectos for discovery, leaving the choice entirely to inference.

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